PUBLICATIONS

 

Books:

 

1.      D.S. Sisodia, R.B. Pachori, and L. Garg, Intelligent data analysis techniques for disease diagnosis and prognosis, Springer, Under processing, 2020.

 

2.      S.K. Pani, S.K. Singh, R.B. Pachori, L. Garg, and X. Zhang, Intelligent data analytics for terror threat prediction: Architectures, methodologies, techniques and applications Wiley-Scrivener Publishing, In press, 2020.

 

3.      D.S. Sisodia, R.B. Pachori, and L. Garg, Advancement of artificial intelligence in healthcare engineering, IGI Global, 2019, ISBN: 9781799821205, In press, 2020.

 

4.      M. Tanveer and R.B. Pachori, Machine intelligence and signal analysis, Advances in Intelligent Systems and Computing, Springer, 2018, ISBN: 978-981-13-0923-6.

 

5.      R.B. Pachori and P. Sircar, Non-stationary signal analysis: Methods based on Fourier-Bessel representation, LAP LAMBERT Academic Publishing, Saarbrucken, Germany, 2010, ISBN: 978-3-8433-8807-8.

 

Book Chapters:

 

1.      A. Ullal and R.B. Pachori, Variational mode decomposition based automated diagnosis method for epilepsy using EEG signals, In: S. Day, S.K. Pani, J. Rodrigues, and B. Majhi (Eds.) Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics Techniques and Applications, Biomedical Engineering, CRC Press, 2020. (Invited).

 

2.      P.S. Ramya, K. Yashasvi, A. Anjum, A. Bhattacharyya, and R.B. Pachori, Development of an effective computing framework for classification of motor imagery EEG signals for brain-computer interface, In: S. Jain, M. Sood, and S. Paul (Eds) Advances in Computational Intelligence Techniques, Springer, 2020.

 

3.      R.R. Sharma, P. Meena, and R.B. Pachori, Enhanced time-frequency representation based on variational mode decomposition and Wigner-Ville distribution, In: S. Jain and S. Paul (Eds.) Recent Trends in Image and Signal Processing in Computer Vision, Springer, 2020.

 

4.      D. Bhati, A. Raikwar, R.B. Pachori, and V.M. Gadre, Three channel wavelet filter banks with minimal time frequency spread for classification of seizure-free and seizure EEG signals, In: D.S. Sisodia, R.B. Pachori, and L. Garg (Eds.) Advancement of Artificial Intelligence in Healthcare Engineering, IGI Global, 2020.

 

5.      R. Singh and R.B. Pachori, Iterative filtering based automated method for detection of normal and ALS EMG signals, In: S. Jain and S. Paul (Eds.) Recent Trends in Image and Signal Processing in Computer Vision, Springer, 2020.

 

6.      R. Sharma, P. Sircar, and R.B. Pachori, Automated seizures classification using deep neural network based on autoencoder, In: D.S. Sisodia, R.B. Pachori, and L. Garg (Eds.) Advancement of Artificial Intelligence in Healthcare Engineering, IGI Global, 2020.

 

7.      R.B. Pachori and V. Gupta, Biomedical engineering fundamentals, In: F. Firouzi, K. Chakrabarty, and S. Nassif (Eds.) Intelligent Internet of Things: From Device, to Fog, and Cloud, Springer, 2020.

 

8.      R. Sharma, P. Sircar, and R.B. Pachori, Computer-aided diagnosis of epilepsy using bispectrum of EEG signals, In: S. Paul (Ed.) Application of Biomedical Engineering in Neuroscience, Springer, 2019.

 

9.      R.R. Sharma, M. Kumar, and R.B. Pachori, Classification of EMG signals using eigenvalue decomposition based time-frequency representation, In: N. Sriraam (Ed.) Biomedical and Clinical Engineering for Healthcare Advancement, IGI Global, 2019.

 

10.  A. Agrawal, L. Garg, E.E. Audu, R.B. Pachori, and J.H.G. Dauwels, Early detection of epileptic seizures based on scalp EEG signals, In: K.C. Santosh, S. Antani, D.S. Guru, and N. Dey (Eds.) Medical imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques, CRC Press, 2019.

 

11.  V. Gupta, A. Bhattacharyya, and R.B. Pachori, Automated identification of epileptic seizures from EEG signals using FBSE-EWT method, In: G.R. Naik (Ed.) Biomedical Signal Processing-Advances in Theory, Algorithms and Applications, Springer, 2019.

 

12.  D. Bhati, R.B. Pachori, M. Sharma, and V.M. Gadre, Automated detection of seizure and nonseizure EEG signals using two-band biorthogonal wavelet filter banks, In: G.R. Naik (Ed.) Biomedical Signal Processing-Advances in Theory, Algorithms and Applications, Springer, 2019.

 

13.  R. Sharma and R.B. Pachori, Automated classification of focal and non-focal EEG signals based on bivariate empirical mode decomposition, In: M.H. Kolekar and V. Kumar (Eds.) Biomedical Signal and Image Processing in Patient Care, IGI Global, 2017.

 

14.  R.B. Pachori, R. Sharma, and S. Patidar, Classification of normal and epileptic seizure EEG signals based on empirical mode decomposition, In: Q. Zhu and A.T. Azar (Eds.) Complex System Modelling and Control through Intelligent Soft Computations, Studies in Fuzziness and Soft Computing, Springer International Publishing, Switzerland, 2015.

 

15.  S. Patidar and R.B. Pachori, Classification of heart disorders based on tunable-Q wavelet transform of cardiac sound signals, In: A.T. Azar and S. Vaidyanathan (Eds.) Chaos Modelling and Control Systems Design, Studies in Computational Intelligence, Springer International Publishing, Switzerland, 2015.

 

16.  V. Bajaj and R.B. Pachori, Detection of human emotions using features based on the multiwavelet transform of EEG signals, In: A.E. Hassanien and A.T. Azar (Eds.) Brain-Computer Interfaces: Current Trends and Applications, Intelligent Systems Reference Library, Springer International Publishing, Switzerland, 2015.

 

Journal Papers:

 

1.      T. Siddharth, P. Gajbhiye, R.K. Tripathy, R.B. Pachori, EEG based detection of focal seizure area using FBSE-EWT rhythm and SAE-SVM network, IEEE Sensors Journal, In press, 2020.

 

2.      B. Fatimaha, P. Singh, A. Singhal, and R.B. Pachori, Detection of apnea events from ECG segments using Fourier decomposition method, Biomedical Signal Processing and Control, In press, 2020.

 

3.      R.U. Khan, M. Tanveer, and R.B. Pachori, A novel method for the classification of Alzheimer's disease from normal controls using MRI, Expert Systems, In press, 2020.

 

4.      A. Nishad and R.B. Pachori, Classification of epileptic electroencephalogram signals using tunable-Q wavelet transform based filter-bank, Journal of Ambient Intelligence and Humanized Computing, In press, 2020.

 

5.      A, Nishad, R.B. Pachori, and U.R. Acharya, Application of TQWT filter-bank for sleep apnea screening using ECG signals, Journal of Ambient Intelligence and Humanized Computing, In press, 2020.

 

6.      J.A. de la O Sema, M.R.A. Patemina, A.Z. Mendez, R.K. Tripathy, and R.B. Pachori, EEG-rhythm specific Taylor-Fourier filter bank implemented with O-splines for the detection of epilepsy using EEG signals, IEEE Sensors Journal, vol. 20, issue 02, pp. 6542-6551, June 2020.

 

7.      R. Sharma, R.B. Pachori, and P. Sircar, Seizures classification based on higher order statistics and deep neural network, Biomedical Signal Processing and Control, vol. 59, 101921, May 2020.

 

8.      A.K. Shukla, R.K. Pandey, and R.B. Pachori, A fractional filter and centerline detection based efficient algorithm for retinal blood vessel segmentation, Biomedical Signal Processing and Control, vol. 59, 101883, May 2020.

 

9.      A. Anuragi, D. Sisodia, and RB Pachori, Automated alcoholism detection using Fourier-Bessel series expansion based empirical wavelet transform, IEEE Sensors Journal, vol. 20, issue 9, pp. 4914-4924, May 2020.

 

10.  P. Gajbhiye, R.K. Tripathy, and R.B. Pachori Elimination of ocular artifacts from single channel EEG signals using FBSE-EWT based rhythms, IEEE Sensors Journal, vol. 20, issue 07, pp. 3687-3696, April 2020.

 

11.  R. Sharma, R.B. Pachori, P. Sircar, Automated emotion recognition based on higher order statistics and deep learning algorithm, Biomedical Signal Processing and Control, vol. 58, 101867, pp. 1-10, April 2020.

 

12.  D.R. Nayak, R. Dash, B. Majhi, R.B. Pachori, and Y. Zhang, A deep stacked random vector functional link network autoencoder for diagnosis of brain abnormalities and breast cancer, Biomedical Signal Processing and Control, vol. 58, 101860, pp. 1-11, April 2020.

 

13.  M. Srirangan, R.K. Tripathy, and R.B. Pachori, Time-frequency domain deep convolutional neural network for the classification of focal and non-focal EEG signals, IEEE Sensors Journal, vol. 20, issue 06, pp. 3078-3086, March 2020.

 

14.  R. Sharma, P. Sircar, and R.B. Pachori, Automated focal EEG signal detection based on third order cumulant function, Biomedical Signal Processing and Control, vol. 58, 101856, pp. 1-8, April 2020.

 

15.  R.R. Sharma, A. Kalyani, and R.B. Pachori, An empirical wavelet transform based approach for cross-terms free Wigner-Ville distribution, Signal, Image, and Video Processing, vol. 14, pp. 249-256, March 2020.

 

16.  A. Singhal, P. Singh, B. Fatimah, and R.B. Pachori, An efficient removal of powerline interference and baseline wander from ECG signals by employing Fourier decomposition technique, Biomedical Signal Processing and Control, vol. 57, 101741, pp. 1-8, March 2020.

 

17.  A.K. Shukla, R. Pandey, S. Yadav, and R.B. Pachori, Generalized fractional filter based algorithm for image denoising, Circuits, Systems, and Signal Processing, vol. 39, issue 01, pp. 363-390, January 2020.

 

18.  D.S. Ramteke, A. Parey, and R.B. Pachori, Automated gear fault detection of micron level wear in bevel gears using variational mode decomposition, Journal of Mechanical Science and Technology, vol. 33, no. 12, pp. 5769-5777, December 2019.

 

19.  P. Gaur, K. McCreadie, R.B. Pachori, H. Wang, and G. Prasad, Tangent space features based transfer learning classification model for two-class motor imagery brain-computer interface, International Journal of Neural Systems, vol. 29, no. 10, 1950025, December 2019.

 

20.  T. Siddharth, R.K. Tripathy, and R.B. Pachori, Discrimination of focal and non-focal seizures from EEG signals using sliding mode singular spectrum analysis, IEEE Sensors Journal, vol. 19, issue 24, pp. 12286-12296, December 2019.

 

21.  S.K. Ghosh, R.K. Tripathy, R.N. Ponnalagu, and R.B. Pachori, Automated detection of heart valve disorders from PCG signal using time-frequency magnitude and phase features, IEEE Sensors Letters, vol. 3, issue 12, pp. 1-4, December 2019.

 

22.  R.K. Tripathy, A. Bhattacharyya, and R.B. Pachori, Localization of myocardial infarction from multi lead electrocardiogram signals using multiscale convolution neural network, IEEE Sensors Journal, vol. 19, no. 23, pp. 11437-11448, December 2019.

 

23.  D.K. Agrawal, B.S. Kirar, and R.B. Pachori, Automated glaucoma detection using quasi-bivariate variational mode decomposition from fundus images, IET Image Processing, vol. 13, issue 13, pp. 2401-2408, November 2019.

 

24.  P. Gajbhiye, R.K. Tripathy, A. Bhattacharyya, and R.B. Pachori, Novel approaches for the removal of motion artifact from EEG signals, IEEE Sensors Journal, vol. 19, issue 02, pp. 10600-10608, November 2019.

 

25.  V. Gupta and R.B. Pachori, Epileptic seizure identification using entropy of FBSE based EEG rhythms, Biomedical Signal Processing and Control, vol. 53, 101569, pp. 1-11, August 2019.

 

26.  P. Gaur, R.B. Pachori, H. Wang, and G. Prasad, An automatic subject specific intrinsic mode function selection for enhancing two-class EEG based motor imagery-brain computer interface, IEEE Sensors Journal, vol. 19, no. 16, pp. 6938-6947, August 2019.

 

27.  R. Katiyar, V. Gupta, and R.B. Pachori, FBSE-EWT-based approach for the determination of respiratory rate from PPG signals, IEEE Sensors Letters, vol. 03, no. 07, article sequence no. 7001604, July 2019.

 

28.  A. Bhattacharyya, R. Ranta, S. Le Cam, V. Louis-Dorr, L. Tyvaert, S. Colnat-Coulbois, L. Maillard, and R. B. Pachori, A multi-channel approach for cortical stimulation artefact suppression in depth EEG signals using time-frequency and spatial filtering, IEEE Transactions on Biomedical Engineering, vol. 66, issue 07, pp. 1915-1926, July 2019.

 

29.  R.K. Tripathy, A. Bhattacharyya, and R.B. Pachori, A novel approach for detection of myocardial infarction from ECG signals of multiple electrodes, IEEE Sensors Journal, vol. 19, issue 12, pp. 4509-4517, June 2019.

 

30.  R.R. Sharma, M. Kumar, and R.B. Pachori, Joint time-frequency domain based CAD disease sensing system using ECG signals, IEEE Sensors Journal, vol. 09, no. 10, pp. 3912-3920, May 2019.

 

31.  R.R. Sharma, A. Kumar, R.B. Pachori, and U.R. Acharya, Accurate automated detection of congestive heart failure using eigenvalue decomposition based features extracted from HRV signals, Biocybernetics and Biomedical Engineering, vol. 39, issue 02, pp. 312-327, April-June 2019.

 

32.  A. Nishad, R.B. Pachori, and U.R. Acharya, Automated classification of hand movements using tunable-Q wavelet transform based filter-bank with surface electromyogram signals, Future Generation Computer Systems, vol. 93, pp. 96-110, April 2019.

 

33.  V. Gupta, M.D. Chopda, and R.B. Pachori, Cross-subject emotion recognition using flexible analytic wavelet transform from EEG signals, IEEE Sensors Journal, vol. 19, no. 06, pp. 2266-2274, March 2019.

 

34.  R. Sharma, P. Sircar, R.B. Pachori, S.V. Bhandary, and U.R. Acharya, Automated glaucoma detection using center slice of higher order statistics, Journal of Mechanics in Medicine and Biology, vol. 19, no. 01, 1940011, February 2019.

 

35.  R. Sharma, P. Sircar, and R.B. Pachori, A new technique for classification of focal and non-focal EEG signals using higher order spectra, Journal of Mechanics in Medicine and Biology, vol. 19, no. 01, 1940010, February 2019.

 

36.  S. Maheshwari, V. Kanhangad, R.B. Pachori, S.V. Bhandary, and U.R. Acharya, Automated glaucoma diagnosis using bit-plane slicing and local binary pattern techniques, Computers in Biology and Medicine, vol. 105, pp. 72-80, February 2019.

 

37.  R.R. Sharma, P. Varshney, R.B. Pachori, and S.K. Vishvakarma, Automated system for epileptic EEG detection using iterative filtering, IEEE Sensors Letters, vol. 2, issue 4, article sequence no. 7001904, December 2018.

 

38.  R.R. Sharma and R.B. Pachori, Improved eigenvalue decomposition-based approach for reducing cross-terms in Wigner-Ville distribution, Circuits, Systems, and Signal Processing, vol. 37, issue 08, pp. 3330-3350, August 2018.

 

39.  R.R. Sharma and R.B. Pachori, Baseline wander and power line interference removal from ECG signals using eigenvalue decomposition, Biomedical Signal Processing and Control, vol. 45, pp. 33-49, August 2018.

 

40.  R.R. Sharma and R.B. Pachori, Eigenvalue decomposition of Hankel matrix-based time-frequency representation of complex signals, Circuits, Systems, and Signal Processing, vol. 37, issue 08, pp. 3313-3329, August 2018.

 

41.  D. Bhati, R.B. Pachori, M. Sharma, and V.M. Gadre, Design of time-frequency localized two-band orthogonal wavelet filter banks, Circuits, Systems and Signal Processing, vol. 37, issue 08, pp. 3295-3312, August 2018.

 

42.  A. Bhattacharyya, L. Singh, and R.B. Pachori, Fourier-Bessel series expansion based empirical wavelet transform for analysis of non-stationary signals, Digital Signal Processing, vol. 78, pp. 185-196, July 2018.

 

43.  M. Kumar, R.B. Pachori, and U.R. Acharya, Automated diagnosis of atrial fibrillation ECG signals using entropy features extracted from flexible analytic wavelet transform, Biocybernetics and Biomedical Engineering, vol. 38, issue 03, pp. 564-573, May 2018.

 

44.  M. Sharma, P. Sharma, R.B. Pachori, and U.R. Acharya, Dual tree complex wavelet transform based features for automated alcoholism identification, International Journal of Fuzzy Systems, vol. 20, issue 04, pp. 1297-1308, April 2018.

 

45.  P. Gaur, R.B. Pachori, H. Wang, and G. Prasad, A multi-class EEG-based BCI classification using multivariate empirical mode decomposition based filtering and Riemannian geometry, Expert Systems with Applications, vol. 95, pp. 201-211, April 2018.

 

46.  A. Bhattacharyya, M. Sharma, R.B. Pachori, P. Sircar, and U.R. Acharya, A novel approach for automated detection of focal EEG signals using empirical wavelet transform, Neural Computing and Applications, vol. 29, issue 8, pp. 47-57, April 2018.

 

47.  R.R. Sharma and R.B. Pachori, Time-frequency representation using IEVDHM-HT with application to classification of epileptic EEG signals, IET Science, Measurement & Technology, vol. 12, issue 01, pp. 72-82, January 2018.

 

48.  M. Sharma and R.B. Pachori, A novel approach to detect epileptic seizures using a combination of tunable-Q wavelet transform and fractal dimension, Journal of Mechanics in Medicine and Biology, vol. 17, no. 07, 1740003, 20 pages, November 2017.

 

49.  P. Singh and R.B. Pachori, Classification of focal and non-focal EEG signals using features derived from Fourier-based rhythms, Journal of Mechanics in Medicine and Biology, vol. 17, no. 07, 1740002, 16 pages, November 2017.

 

50.  R. Sharma, R.B. Pachori, and A. Upadhyay, Automatic sleep stages classification based on iterative filtering of electroencephalogram signals, Neural Computing and Applications, vol. 28, issue 10, pp. 2959-2978, October 2017.

 

51.  D. Bhati, R.B. Pachori, and V.M. Gadre, A novel approach for time-frequency localization of scaling functions and design of three-band biorthogonal linear phase wavelet filter banks, Digital Signal Processing, vol. 69, pp. 309-322, October 2017.

 

52.  M. Kumar, R.B. Pachori, and U.R. Acharya, Automated diagnosis of myocardial infarction ECG signals using sample entropy in flexible analytic wavelet transform framework, Entropy, vol. 19 (9), 488, pages 14, September 2017.

 

53.  A. Bhattacharyya and R.B. Pachori, A multivariate approach for patient specific EEG seizure detection using empirical wavelet transform, IEEE Transactions on Biomedical Engineering, vol. 64, no. 09, pp. 2003-2015, September 2017.

 

54.  S. Maheshwari, R.B. Pachori, V. Kanhangad, S.V. Bhandary, and U.R. Acharya, Iterative variational mode decomposition based automated detection of glaucoma using fundus images, Computers in Biology and Medicine, vol. 88, pp. 142-147, September 2017.

 

55.  M.K. Saxena, S.D.V.S. Jagannadha Raju, R. Arya, R.B. Pachori, and S. Kher, Instantaneous area based on-line detection of bend generated error in a Raman optical fiber distributed temperature sensor, IEEE Sensors Letters, vol. 01, no. 4, article sequence no. 7000204, August 2017.

 

56.  A. Upadhyay, M. Sharma, and R.B. Pachori, Determination of instantaneous fundamental frequency of speech signals using variational mode decomposition, Computers and Electrical Engineering, vol. 62, pp. 630-647, August 2017.

 

57.  A.K. Tiwari, R.B. Pachori, V. Kanhangad, and B.K. Panigrahi, Automated diagnosis of epilepsy using key-points based local binary pattern of EEG signals, IEEE Journal of Biomedical and Health Informatics, vol. 21, issue 4, pp. 888-896, July 2017.

 

58.  V. Gupta, T. Priya, R.B. Pachori, and U.R. Acharya, Automated detection of focal EEG signals using features extracted from flexible analytic wavelet transform, Pattern Recognition Letters, vol. 94, pp. 180-188, July 2017.

 

59.  M. Sharma, R.B. Pachori, and U.R. Acharya, A new approach to characterize epileptic seizures using analytic time-frequency flexible wavelet transform and fractal dimension, Pattern Recognition Letters, vol. 94, pp. 172-179, July 2017.

 

60.  M. Sharma, P.V. Achuth, R.B. Pachori, and V.M. Gadre, A parametrization technique to design joint time-frequency optimized discrete-time biorthogonal wavelet bases, Signal Processing, vol. 135, pp. 107-120, June 2017.

 

61.  R. Sharma, M. Kumar, R.B. Pachori, and U.R. Acharya, Decision support system for focal EEG signals using tunable-Q wavelet transform, Journal of Computational Science, vol. 20, pp. 52-60, May 2017.

 

62.  S. Maheshwari, R.B. Pachori, and U.R. Acharya, Automated classification of glaucoma using empirical wavelet transform and correntropy features extracted from fundus images, IEEE Journal of Biomedical and Health Informatics, vol. 21, no. 03, pp. 803-813, May 2017.

 

63.  M. Sharma, A. Dhere, R.B. Pachori, and V.M. Gadre, Optimal duration-bandwidth localized antisymmetric biorthogonal wavelet filters, Signal Processing, vol. 134, pp. 87-99, May 2017.

 

64.  A. Bhattacharyya, R.B. Pachori, A. Upadhyay, and U.R. Acharya, Tunable-Q wavelet transform based multiscale entropy measure for automated classification of epileptic EEG signals, Applied Sciences, vol. 7(4), 385, pages: 18, April 2017.

 

65.  A.K. Tiwari, V. Kanhangad, and R.B. Pachori, Histogram refinement for texture descriptor based image retrieval, Signal Processing: Image Communication, vol. 53, pp. 73-85, April 2017.

 

66.  A. Bhattacharyya, R.B. Pachori, and U.R. Acharya, Tunable-Q wavelet transform based multivariate sub-band fuzzy entropy with application to focal EEG signal analysis, Entropy, vol. 19 (3), 99, pages: 14, March 2017.

 

67.  A. Upadhyay and R.B. Pachori, Speech enhancement based on mEMD-VMD method, Electronics Letters, vol. 53, issue 07, pp. 502-504, March 2017.

 

68.  D. Bhati, M. Sharma, R.B. Pachori, and V.M. Gadre, Time-frequency localized three-band biorthogonal wavelet filter bank using semidefinite relaxation and nonlinear least squares with epileptic seizure EEG signal classification, Digital Signal Processing, vol. 62, pp. 259-273, March 2017.

 

69.  M. Kumar, R.B. Pachori, and U.R. Acharya, Use of accumulated entropies for automated detection of congestive heart failure in flexible analytic wavelet transform framework based on short-time HRV signals, Entropy, 19 (3), 92, pages: 21, February 2017.

 

70.  M. Sharma, A. Dhere, R.B. Pachori, and U.R. Acharya, An automatic detection of focal EEG signals using new class of time-frequency localized orthogonal wavelet filter banks, Knowledge-Based Systems, vol. 118, pp. 217-227, February 2017.

 

71.  S. Patidar, R.B. Pachori, A. Upadhyay, and U.R. Acharya, An integrated alcoholic index using tunable-Q wavelet transform based features extracted from EEG signals for diagnosis of alcoholism, Applied Soft Computing, vol. 50, pp. 71-78, January 2017.

 

72.  M. Kumar, R.B. Pachori, and U.R. Acharya, Characterization of coronary artery disease using flexible analytic wavelet transform applied on ECG signals, Biomedical Signal Processing and Control, vol. 31, pp. 301-308, January 2017.

 

73.  D. Bhati, M. Sharma, R.B. Pachori, S.S. Nair, and V.M. Gadre, Design of time-frequency optimal three-band wavelet filter banks with unit Sobolev regularity using frequency domain sampling, Circuits, Systems & Signal Processing, vol. 35, issue 12, pp. 4501-4531, December 2016.

 

74.  M. Kumar, R.B. Pachori, and U.R. Acharya, An efficient automated technique for CAD diagnosis using flexible analytic wavelet transform and entropy features extracted from HRV signals, Expert Systems with Applications, vol. 63, pp. 165-172, November 2016.

 

75.  M. Sharma, D. Bhati, S. Pillai, R.B. Pachori, and V.M. Gadre, Design of time-frequency localized filter banks: Transforming non-convex problem into convex via semidefinite relaxation technique, Circuits, Systems & Signal Processing, vol. 35, issue 10, pp. 3716-3733, October 2016.

 

76.  R.B. Pachori and A. Nishad, Cross-terms reduction in Wigner-Ville distribution using tunable-Q wavelet transform, Signal Processing, vol. 120, pp. 288-304, March 2016.

 

77.  M.K. Saxena, S.D.V.S.J. Raju, R. Arya, R.B. Pachori, S.V.G. Ravindranath, S. Kher, and S.M. Oak, Empirical mode decomposition based detection of bend induced error and its correction in a Raman fiber distributed temperature sensor, IEEE Sensors Journal, vol. 16, no. 5, pp. 1243-1252, March 2016.

 

78.  R.B. Pachori, M. Kumar, K. Shashank, P. Avinash, and U.R. Acharya, An improved online paradigm for screening of diabetic patients using RR interval signals, Journal of Mechanics in Medicine and Biology, vol. 16, no. 01, 1640003, 23 pages, February 2016.

 

79.  S. Sood, M. Kumar, R.B. Pachori, and U.R. Acharya, Application of empirical mode decomposition-based features for analysis of normal and CAD heart rate signals, Journal of Mechanics in Medicine and Biology, vol. 16, no. 01, 1640002, 20 pages, February 2016.

 

80.  O. Sahu, V. Anand, V. Kanhangad, and R.B. Pachori, Classification of magnetic resonance brain images using bi-dimensional empirical mode decomposition and autoregressive model, Biomedical Engineering Letters, vol. 5, issue 4, pp. 311-320, December 2015.

 

81.  P. Jain and R.B. Pachori, An iterative approach for decomposition of multi-component non-stationary signals based on eigenvalue decomposition of the Hankel matrix, Journal of the Franklin Institute, vol. 352, issue 10, pp. 4017-4044, October 2015.

 

82.  A.S. Hood, R.B. Pachori, V.K. Reddy, and P. Sircar, Parametric representation of speech employing multi-component AFM signal model, International Journal of Speech Technology, vol. 18, issue 03, pp. 287-303, September 2015.

 

83.  R. Sharma, R.B. Pachori, and U.R. Acharya, An integrated index for the identification of focal electroencephalogram signals using discrete wavelet transform and entropy measures, Entropy, vol. 17, issue 8, pp. 5218-5240, July 2015.

 

84.  A. Upadhyay and R.B. Pachori, Instantaneous voiced/non-voiced detection in speech signals based on variational mode decomposition, Journal of the Franklin Institute, vol. 352, issue 7, pp. 2679-2707, July 2015.

 

85.  S. Patidar, R.B. Pachori, and U.R. Acharya, Automated diagnosis of coronary artery disease using tunable-Q wavelet transform applied on heart rate signals, Knowledge Based Systems, vol. 82, pp. 1-10, July 2015.

 

86.  R.B. Pachori, P. Avinash, K. Shashank, R. Sharma, and U.R. Acharya, Application of empirical mode decomposition for the analysis of normal and diabetic RR-interval signals, Expert Systems with Applications, vol. 42, issue 9, pp. 4567-4581, June 2015.

 

87.  S. Patidar, R.B. Pachori, and N. Garg, Automatic diagnosis of septal defects based on tunable-Q wavelet transform of cardiac sound signals, Expert Systems with Applications, vol. 42, issue 7, pp. 3315-3326, May 2015.

 

88.  M.K. Saxena, S.D.V.S.J. Raju, R. Arya, R.B. Pachori, S.V.G. Ravindranath, S. Kher, and S.M. Oak, Empirical mode decomposition based dynamic error correction in SS covered 62.5/125 \micro m optical fiber based distributed temperature sensor, Optics & Laser Technology, vol. 67, pp. 107-118, April 2015.

 

89.  R. Sharma, R.B. Pachori, and U.R. Acharya, Application of entropy measures on intrinsic mode functions for automated identification of focal electroencephalogram signals, Entropy, vol. 17, issue 2, pp. 669-691, February 2015.

 

90.  R. Sharma and R.B. Pachori, Classification of epileptic seizures in EEG signals based on phase space representation of intrinsic mode functions, Expert Systems with Applications, vol. 42, issue 3, pp. 1106-1117, February 2015.

 

91.  T.S. Kumar, V. Kanhangad, and R.B. Pachori, Classification of seizure and seizure-free EEG signals using local binary patterns, Biomedical Signal Processing and Control, vol. 15, pp. 33-40, January 2015.

 

92.  M.K. Saxena, S.D.V.S.J. Raju, R. Arya, R.B. Pachori, S.V.G. Ravindranath, S. Kher, and S.M. Oak, Raman optical fiber distributed temperature sensor using wavelet transform based simplified signal processing of Raman backscattered signals, Optics & Laser Technology, vol. 65, pp. 14-24, January 2015.

 

93.  S. Patidar and R.B. Pachori, Classification of cardiac sound signals using constrained tunable-Q wavelet transform, Expert Systems with Applications, vol. 41, pp. 7161-7170, November 2014.

 

94.  P. Jain and R.B. Pachori, Event-based method for instantaneous fundamental frequency estimation from voiced speech based on eigenvalue decomposition of Hankel matrix, IEEE/ACM Transactions on Audio, Speech and Language Processing, vol. 22. issue 10, pp. 1467-1482, October 2014.

 

95.  A. Parey and R.B. Pachori, Gear fault diagnosis based on central tendency measure of intrinsic mode functions, International Journal of COMADEM, vol. 17, no. 3, pp. 15-22, July 2014.

 

96.  R.B. Pachori and S. Patidar, Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions, Computer Methods and Programs in Biomedicine, vol. 113, issue 2, pp. 494-502, February 2014.

 

97.  V. Joshi, R.B. Pachori, and A. Vijesh, Classification of ictal and seizure-free EEG signals using fractional linear prediction, Biomedical Signal Processing and Control, vol. 9, pp. 1-5, January 2014.

 

98.  S. Patidar and R.B. Pachori, Constrained tunable-Q wavelet transform based analysis of cardiac sound signals, AASRI Procedia, vol. 4, pp. 57-63, 2013.

 

99.  V. Bajaj and R.B. Pachori, Automatic classification of sleep stages based on the time frequency image of EEG signals, Computer Methods and Programs in Biomedicine, vol. 112, issue 3, pp. 320-328, December 2013.

 

100.                     S. Patidar and R.B. Pachori, Segmentation of cardiac sound signals by removing murmurs using constrained tunable-Q wavelet transform, Biomedical Signal Processing and Control, vol. 8, issue 6, pp. 559-567, November 2013.

 

101.                     P. Jain and R.B. Pachori, Marginal energy density over the low frequency range as a feature for voiced/non-voiced detection in noisy speech signals, Journal of the Franklin Institute, vol. 350, issue 4, pp. 678-716, May 2013.

 

102.                     V. Bajaj and R.B. Pachori, Epileptic seizure detection based on the instantaneous area of analytic intrinsic mode functions of EEG signals, Biomedical Engineering Letters, vol. 3, issue 1, pp. 17-21, March 2013.

 

103.                     V. Bajaj and R.B. Pachori, Classification of seizure and nonseizure EEG signals using empirical mode decomposition, IEEE Transactions on Information Technology in BioMedicine, vol. 16, no. 6, pp. 1135-1142, November 2012.

 

104.                     P. Jain and R.B. Pachori, Time-order representation based method for epoch detection from speech signals, Journal of Intelligent Systems, vol. 21, issue 1, pp. 79-95, February 2012.

 

105.                     A. Parey and R.B. Pachori, Variable cosine windowing of intrinsic mode functions: Application to gear fault diagnosis, Measurement, vol. 45, issue 3, pp. 415-426, April 2012.

 

106.                     R.B. Pachori and V. Bajaj, Analysis of normal and epileptic seizure EEG signals using empirical mode decomposition, Computer Methods and Programs in Biomedicine, vol. 104, issue 3, pp. 373-381, December 2011.

 

107.                     R.B. Pachori and D. Hewson, Assessment of the effects of sensory perturbations using Fourier-Bessel expansion method for postural stability analysis, Journal of Intelligent Systems, vol. 20, issue 2, pp. 167-186, August 2011.

 

108.                     A.F. Mohed, G. Rama Murthy, and R.B. Pachori, Novel orthogonal signal based decomposition of digital signals: Application to sensor fusion, Sensors & Transducers, vol. 114, issue 3, pp. 56-65, March 2010.

 

109.                     R.B. Pachori and P. Sircar, Analysis of multicomponent AM-FM signals using FB-DESA method, Digital Signal Processing, vol. 20, pp. 42-62, January 2010.

 

110.                     R.B. Pachori, Discrimination between ictal and seizure-free EEG signals using empirical mode decomposition, Research Letters in Signal Processing, vol. 2008, Article ID 293056, 5 pages, December 2008.

 

111.                     R.B. Pachori and P. Sircar, EEG signal analysis using FB expansion and second-order linear TVAR process, Signal Processing, vol. 88, no. 2, pp. 415-420, February 2008.

 

112.                     R.B. Pachori and P. Sircar, A new technique to reduce cross terms in the Wigner distribution, Digital Signal Processing, vol. 17, no. 2, pp. 466-474, March 2007.

 

Conference Papers:

 

1.      V.K. Singh and R.B. Pachori, Sliding eigenvalue decomposition for non-stationary signal analysis, International Conference on Signal Processing and Communication (SPCOM), July 2020, Bangalore, India

 

2.      P. Meena, R.R. Sharma, and R.B. Pachori, Cross-term suppression in the Wigner-Ville distribution using variational mode decomposition, 5th International conference on Signal Processing, Computing, and Control (ISPCC-2k19), October 10-12,  2019, Waknaghat, India.

 

3.      P.S. Ramya, K. Yashashvi, A. Anjum, A. Bhattacharyya, and R.B. Pachori, A filtering method for classification of motor-imagery EEG signals for brain-computer interface, 5th International conference on Signal Processing, Computing, and Control (ISPCC-2k19), October 10-12,  2019, Waknaghat, India.

 

4.      V. Gupta, A. Nishad, and R.B. Pachori, Focal EEG signal detection based on constant-bandwidth TQWT filter-banks, 2018 IEEE International Conference on Bioinformatics and Biomedicine, 03-06 December, 2018, Madrid, Spain

 

5.      M. Tanveer, R.B. Pachori and N.V. Victoria, Entropy based features in FAWT framework for automated detection of epileptic seizure EEG signals, 2018 Symposium Series on Computational Intelligence, 18-21 November, 2018, Bengaluru, India.

 

6.      M. Tanveer, R.B. Pachori and N.V. Victoria, Classification of seizure and seizure-free EEG signals using Hjorth parameters, 2018 Symposium Series on Computational Intelligence, 18-21 November, 2018, Bengaluru, India.

 

7.      A. Nishad and R.B. Pachori, Instantaneous fundamental frequency estimation of speech signals using tunable-Q wavelet transform, International Conferences on Signal Processing and Communications (SPCOM), July 16-19, 2018, Bangalore, India.

 

8.      S. Gupta, K. Hari Krishna, R.B. Pachori, and M. Tanveer, Fourier-Bessel series expansion based technique for automated classification of focal and non-focal EEG signals, International Joint Conference on Neural Networks (IJCNN), July 08-13, 2018, Rio, Brazil.

 

9.      A. Bhattacharyya, L. Singh, and R.B. Pachori, Identification of epileptic seizures from scalp EEG signals based on TQWT, International Conference on Machine Intelligence and Signal Processing, December 22-24, 2017, Indore, India.

 

10.  S. Shah, M. Sharma, D. Deb, and R.B. Pachori, An automated alcoholism detection using orthogonal wavelet filter bank, International Conference on Machine Intelligence and Signal Processing, December 22-24, 2017, Indore, India.

 

11.  M. Sharma, P. Sharma, R.B. Pachori, and V.M. Gadre, Double density dual-tree complex wavelet transform based features for automated screening of knee-joint vibroarthrographic signals, International Conference on Machine Intelligence and Signal Processing, December 22-24, 2017, Indore, India.

 

12.  R.R. Sharma, M. Kumar, and R.B. Pachori, Automated CAD identification system using time-frequency representation based on eigenvalue decomposition of ECG signals, International Conference on Machine Intelligence and Signal Processing, December 22-24, 2017, Indore, India.

 

13.  R.R. Sharma, P. Chandra, and R.B. Pachori, Electromyogram signal analysis using eigenvalue decomposition of the Hankel matrix, International Conference on Machine Intelligence and Signal Processing, December 22-24, 2017, Indore, India.

 

14.  M. Dalal, M. Tanveer, and R.B. Pachori, Automated identification system for focal EEG signals using fractal dimension of FAWT based sub-bands signals, International Conference on Machine Intelligence and Signal Processing, December 22-24, 2017, Indore, India.

 

15.  V. Gupta and R.B. Pachori, A new method for classification of focal and non-focal EEG signals, International Conference on Machine Intelligence and Signal Processing, December 22-24, 2017, Indore, India.

 

16.  D. Bhati, R.B. Pachori, and V.M. Gadre, Optimal design of three-band orthogonal wavelet filter bank with stopband energy for identification of epileptic seizure EEG signals, International Conference on Machine Intelligence and Signal Processing, December 22-24, 2017, Indore, India.

 

17.  P. Gaur, R.B. Pachori, H. Wang, and G. Prasad, Comparison analysis: single and multichannel EMD based filtering with application to BCI, International Conference on Machine Intelligence and Signal Processing, December 22-24, 2017, Indore, India.

 

18.  A. Bhattacharyya, V. Gupta and R.B. Pachori, Automated identification of epileptic seizure EEG signals using empirical wavelet transform based Hilbert marginal spectrum, 22nd International Conference on Digital Signal Processing, August 23-25, 2017, London, United Kingdom.

 

19.  V. Gupta, A. Bhattacharyya, and R.B. Pachori, Classification of seizure and non-seizure EEG signals based on EMD-TQWT method, 22nd International Conference on Digital Signal Processing, August 23-25, 2017, London, UK.

 

20.  M. Sharma, R.B. Pachori, and V.M. Gadre, A novel class of optimal time-frequency localized biorthogonal wavelet filter banks for automated identification of epileptic seizures, International Symposium on Computational Mathematics, Optimization, and Computational Intelligence (CMOCI 2017), July 17 - 19, 2017, IIT Indore, Indore, India. (Abstract).

 

21.  M. Tanveer, R.B. Pachori, and M. Dalal, Automated detection of EEG signal based on flexible analytic wavelet transform with an optimal signal length, International Symposium on Computational Mathematics, Optimization, and Computational Intelligence (CMOCI 2017), July 17 - 19, 2017, IIT Indore, Indore, India. (Abstract).

 

22.  P. Gaur, J.S. Bornot, G. Prasad, H. Wang, and R.B. Pachori, Decoding of multi-direction wrist movements using multivariate empirical mode decomposition, MEG UK 2017, March 22-24, 2017, Oxford, UK. (Poster).

 

23.  G. Kaushik, P. Gaur, G. Prasad, H. Wang, and R.B. Pachori, An MEG based multi direction wrist movements analysis using empirical mode decomposition and multivariate empirical mode decomposition, MEG UK 2016, March 22-24, 2017, Oxford, UK. (Poster).

 

24.  D. Joshi, A. Tripathi, R. Sharma, and R.B. Pachori, Computer aided detection of abnormal EMG signals based on tunable-Q wavelet transform, International Conference on Signal Processing & Integrated Networks, February 11-12, 2017, Noida, India.

 

25.  R.R. Sharma and R.B. Pachori, A new method for non-stationary signal analysis using eigenvalue decomposition of the Hankel matrix and Hilbert transform, International Conference on Signal Processing & Integrated Networks, February 11-12, 2017, Noida, India.

 

26.  S. Patidar and R.B. Pachori, Tunable-Q wavelet transform based optimal compression of cardiac sound signals, IEEE Tencon Conference, November 22-25, 2016, Singapore.

 

27.  P. Gaur, R.B. Pachori, H. Wang, and G. Prasad, A multivariate empirical mode decomposition based filtering for subject independent BCI, 27th Irish Signals and Systems Conference, June 21-22, 2016, Derry, UK.

 

28.  P. Gaur, R.B. Pachori, H. Wang, and G. Prasad, Enhanced motor imagery classification in EEG-BCI using multivariate EMD based filtering and CSP features, International Brain-Computer Interface (BCI) Meeting, May 30th -June 3rd, 2016, California, USA.

 

29.  P. Gaur, R.B. Pachori, H. Wang, and G. Prasad, An MEG based BCI for classification of multi direction wrist movements using empirical mode decomposition, MEG UK 2016, March 21-23, 2016, York, UK. (Poster).

 

30.  A. Upadhyay and R.B. Pachori, A new method for determination of instantaneous fundamental frequency from speech signals, IEEE Signal Processing and Signal Processing Education Workshop, 09-12 August, 2015, Salt Lake City, Utah, USA.

 

31.  P. Gaur, R.B. Pachori, H. Wang, and G. Prasad, An empirical mode decomposition based filtering method for classification of motor-imagery EEG signals for enhancing brain-computer interface, The International Joint Conference on Neural Networks, Killarney, Ireland, July 12 - 17, 2015.

 

32.  R.B. Pachori, Automatic diagnosis of epilepsy using non-stationary signal decomposition based methods, International Conference on Significant Advances in Biomedical Engineering, Philadelphia, USA, April 27-29, 2015.

 

33.  A. Mathur, N. Choudhary, A. Upadhyay, and R.B Pachori, Detection of glottal closure instants from voiced speech signals using the Fourier-Bessel series expansion, 4th IEEE International Conference on Communication and Signal Processing, Melmaruvathur, India, 2-4 April, 2015.

 

34.  M. Shah, S. Saurav, R. Sharma, and R.B Pachori, Analysis of epileptic seizure EEG signals using reconstructed phase space of intrinsic mode functions, 9th IEEE International Conference on Industrial and Information Systems, 15-17 December, 2014, Gwalior, India.

 

35.  S. Patidar, R.B. Pachori, and N. Garg, Detection of septal defects from cardiac sound signals using tunable-Q wavelet transform, IEEE International Conference on Digital Signal Processing, 20-23 August, 2014, Hong Kong.

 

36.  T.S. Kumar, V. Kanhangad, and R.B. Pachori, Classification of seizure and seizure-free EEG signals using multi-level local patterns, IEEE International Conference on Digital Signal Processing, 20-23 August, 2014, Hong Kong.

 

37.  R.B. Pachori and J.-L. Kim, Comparison of the health care function by head movement, The 1st International Conference on Contents, Platform, Network and Device, 10 July-13 July, 2014, Pusan, Korea.

 

38.  R. Sharma, R.B. Pachori, and S. Gautam, Empirical mode decomposition based classification of focal and non-focal EEG signals, IEEE International Conference on Medical Biometrics, 30 May-01 June, 2014, Shenzhen, China.

 

39.  V. Bajaj and R.B. Pachori, Human emotion classification from EEG signals using multiwavelet transform, IEEE International Conference on Medical Biometrics, 30 May-01 June, 2014, Shenzhen, China.

 

40.  P.S. Rathore and R.B. Pachori, Instantaneous fundamental frequency estimation of speech signals using DESA in low-frequency region, IEEE International Conference on Signal Processing and Communication, pp. 470-473, 12-14 December, 2013, Noida, India.

 

41.  R. Bodade, R.B. Pachori, A. Gupta, P. Kanani, and D. Yadav, A novel approach for automated skew correction of vehicle number plate using principal component analysis, IEEE International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications, 10-11 October, 2013, Bangalore, India.

 

42.  P. Jain and R.B. Pachori, GCI identification from voiced speech using the eigen value decomposition of Hankel matrix, IEEE 8th International Symposium on Image and Signal Processing and Analysis, pp. 371 - 376, 04-06 September, 2013, Trieste, Italy.

 

43.  P. Kanani, A. Gupta, D. Yadav, R. Bodade, and R.B. Pachori, Vehicle license plate localization using wavelets, IEEE Conference on Information and Communication Technologies, 11-12 April, 2013, Thuckalay, India.

 

44.  S. Patidar and R.B. Pachori, A continuous wavelet transform based method for detecting heart valve disorders using phonocardiograph signals, International Conference on Convergence and Hybrid Information Technology, CCIS 310, pp. 513-520, 23-25 August, 2012, Daejeon, South Korea.

 

45.  V. Bajaj and R.B. Pachori, Separation of rhythms of EEG signals based on Hilbert-Huang transformation with application to seizure detection, International Conference on Convergence and Hybrid Information Technology, LNCS 7425, pp. 493-500, 23-25 August, 2012, Daejeon, South Korea. (Best Paper Award)

 

46.  V. Bajaj and R.B. Pachori, EEG signal classification using empirical mode decomposition and support vector machine, International Conference on Soft Computing for Problem Solving, AISC 131, pp. 623-635, 20-22 December, 2011, Roorkee, India.

 

47.  V. Bajaj and R.B. Pachori, Application of the sample entropy for discrimination between seizure and seizure-free EEG signals, 5th Indian International Conference on Artificial Intelligence, pp. 1232-1247, 14-16 December, 2011, Tumkur, India.

 

48.  P. Jain and R.B. Pachori, A new approach for glottal closure instants detection from speech signals, 5th Indian International Conference on Artificial Intelligence, pp. 1216-1231, 14-16 December, 2011, Tumkur, India.

 

49.  R.B. Pachori and D. Hewson, Identification of time-varying effects of sensory perturbations for postural stability analysis, 5th Indian International Conference on Artificial Intelligence, pp. 1280-1292, 14-16 December, 2011, Tumkur, India.

 

50.  R.B. Pachori, J. Gadewadikar, and O. Kuljaca, Classification of EEG signals based on empirical mode decomposition and Bayesian networks application, Seventy-Fifth Annual Meeting, University of Southern Mississippi, USA, February 17-18, 2011 (Abstract Issue of Journal of the Mississippi Academy of Sciences, vol. 56, no. 1, pp. 101, Jan 2011).

 

51.  A. Parey and R.B. Pachori, Modified empirical mode decomposition process for improved fault diagnosis, 8th IFToMM International Conference on Rotor Dynamics, pp. 261-265, 12-15 September, 2010, Seoul, Korea.

 

52.  R.B. Pachori and S.V. Gangashetty, AM-FM model based approach for detection of glottal closure instants, IEEE International Conference on Information Science, Signal Processing and their Applications, pp. 266-269, 10-13 May, 2010, Kuala Lumpur, Malaysia.

 

53.  R.B. Pachori and S.V. Gangashetty, Detection of voice onset time using FB expansion and AM-FM model, IEEE International Conference on Information Science, Signal Processing and their Applications, 149-152, 10-13 May, 2010, Kuala Lumpur, Malaysia.

 

54.  S. Chhabra, R. Bajaj, R.B. Pachori, and R.N. Biswas, Features based on Fourier-Bessel expansion for application of speaker identification system, Proceedings Indian Conference for Academic Research by Undergraduate Students, 26-28 March, 2010, IIT Kanpur, India.

 

55.  P. Sircar, R.B. Pachori, and R. Kumar, Analysis of rhythms of EEG signals using orthogonal polynomial approximation, ACM International Conference on Convergence and Hybrid Information Technology, pp. 176-180, 27-29 August, 2009, Daejeon, South Korea.

 

56.  R.B. Pachori, D. Hewson, H. Snoussi, and J. Duchne, Postural time-series analysis using empirical mode decomposition and second-order difference plots, IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 537-540, 19-24 April, 2009, Taipei, Taiwan.

 

57.  R.B. Pachori, D. Hewson, H. Snoussi, and J. Duchene, Analysis of center of pressure signals using empirical mode decomposition and Fourier-Bessel expansion, IEEE Tencon Conference, Article no. 4766596, 18-21 November, 2008, Hyderabad, India.

 

58.  R.B. Pachori and P. Sircar, Time-frequency analysis using time-order representation and Wigner distribution, IEEE Tencon Conference, Article no. 4766782, 18-21 November, 2008, Hyderabad, India.

 

59.  R.B. Pachori and P. Sircar, Modeling of multicomponent AM-FM signals using FB expansion and linear TVAR process, 16th European Signal Processing Conference, 25-29 August, 2008, Lausanne, Switzerland.

60.  R.B. Pachori and P. Sircar, Speech analysis using Fourier-Bessel expansion and discrete energy separation algorithm, IEEE Digital Signal Processing Workshop and Workshop on Signal Processing Education, pp. 423-428, 24-27 September, 2006, Wyoming, USA.

 

61.  R.B. Pachori and P. Sircar, Analysis of multicomponent nonstationary signals using Fourier-Bessel transform and Wigner distribution, 14th European Signal Processing Conference, 04-08 September, 2006, Florence, Italy.

 

62.  J. Qumar and R.B. Pachori, A novel technique for merging of multisensor and defocussed images using multiwavelets, IEEE Tencon Conference, pp. 1733-1738, 22-24 November, 2005, Melbourne, Australia.

 

63.  R.B. Pachori and P. Sircar, A novel technique to reduce cross terms in the squared magnitude of the wavelet transform and the short time Fourier transform, IEEE International Workshop on Intelligent Signal Processing, pp. 217-222, 01-03 September, 2005, Faro, Portugal.

 

64.  R.B. Pachori and P. Sircar, Modeling of time varying AR process using nonlinear energy operator, IEEE 8th International Symposium on Signal Processing and its Applications, pp. 643-646, 28-30 August, 2005, Sydney, Australia.

 

65.  R.B. Pachori and P. Sircar, A new technique to reduce cross terms in the Wigner distribution, 11th National Conference on Communications, pp. 427-431, 28-30 January, 2005, IIT Kharagpur, India.