This book provides emphasis on brain and behaviour computing with different modalities available such as signal and image processing, data science, statistics, distributed computing including basics, model, algorithms, case studies, and research scope. It further explains brain signals sources, signal processing, manipulation and transformations.
This book provides emphasis on brain and behaviour computing with different modalities available such as signal and image processing, data science, statistics, distributed computing including basics, model, algorithms, case studies, and research scope. It further explains brain signals sources, signal processing, manipulation and transformations.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Mridu Sahu has completed her graduation in Computer Science and Engineering in 2004 from Maulana Azad National Institute of Technology, Bhopal. She completed her post - graduation Master of Technology in Computer Science and Engineering from RIT, Raipur in 2011 and completed the Ph.D. in Computer Science and Engineering in 2018 from National Institute of Technology Raipur, India. She is having more than 10-year experiences in teaching, presently she is working as Assistant professor in department of Information Technology, NIT Raipur. She has published more than 25 research articles in various journals and conferences and book chapters in the field of Data Mining, Brain Computer Interface, Sensor devices and Visual Mining Techniques. G R Sinha is Adjunct Professor at International Institute of Information Technology (IIIT) Bangalore and currently deputed as Professor at Myanmar Institute of Information Technology (MIIT) Mandalay Myanmar. He obtained his B.E. (Electronics Engineering) and M.Tech. (Computer Technology) with Gold Medal from National Institute of Technology Raipur, India. He received his Ph.D. in Electronics & Telecommunication Engineering from Chhattisgarh Swami Vivekanand Technical University (CSVTU) Bhilai, India. He is Visiting Professor (Honorary) in Sri Lanka Technological Campus Colombo for one year 2019-2020. He has published 250 research papers, book chapters and books at International and National level that includes Biometrics published by Wiley India, a subsidiary of John Wiley; Medical Image Processing published by Prentice Hall of India and 05 Edited books on Cognitive Science-Two Volumes (Elsevier), Optimization Theory (IOP) and Biometrics (Springer). He is active reviewer and editorial member of more than 12 Reputed International Journals such IEEE Transactions on Image Processing, Elsevier Computer Methods and Programs in Biomedicine, Springer Journal of Neural Computing and Applications etc. He has teaching and research experience of 21 years. He has been Dean of Faculty and Executive Council Member of CSVTU and currently a member of Senate of MIIT. Dr Sinha has been delivering ACM lectures as ACM Distinguished Speaker in the field of DSP since 2017 across the world. His few more important assignments include Expert Member for Vocational Training Programme by Tata Institute of Social Sciences (TISS) for Two Years (2017-2019); Chhattisgarh Representative of IEEE P Sub-Section Executive Council (2016-2019); Distinguished Speaker in the field of Digital Image Processing by Computer Society of India (2015). He is recipient of many awards and recognitions like TCS Award 2014 for Outstanding contributions in Campus Commune of TCS, Rajaram Bapu Patil ISTE National Award 2013 for Promising Teacher in Technical Education by ISTE New Delhi, Emerging Chhattisgarh Award 2013, Engineer of the Year Award 2011, Young Engineer Award 2008, Young Scientist Award 2005, IEI Expert Engineer Award 2007, ISCA Young Scientist Award 2006 Nomination and Deshbandhu Merit Scholarship for 05 years. He served as Distinguished IEEE Lecturer in IEEE India council for Bombay section. He is Senior Member of IEEE and Fellow of IETE India.
Inhaltsangabe
1. Simulation Tools for Brain Signal Analysis 2. Processing Techniques and Analysis of Brain Sensor Data Using Electroencephalography 3. Application of Machine-Learning Techniques in Electroencephalography Signals 4. Revolution of Brain Computer Interface: An Introduction 5. Signal Modeling Using Spatial Filtering and Matching Wavelet Feature Extraction for Classification of Brain Activity Pattern 6. Study and Analysis of the Visual P300 Speller on Neurotypical Subjects 7. Effective Brain Computer Interface Based on the Adaptive-Rate Processing and Classification of Motor Imagery Tasks 8. EEG-Based BCI Systems for Neurorehabilitation Applications 9. Scalp EEG Classification Using TQWT-Entropy Features for Epileptic Seizure Detection 10. An Efficient Single-Trial Classification Approach for Devanagari Script-Based Visual P300 Speller Using Knowledge Distillation and Transfer Learning 11. Deep Learning Algorithms for Brain Image Analysis 12. Evolutionary Optimization Based Two Dimensional Elliptical FIR Filters for Skull Stripping in Brain Imaging and Disorder Detection 13. EEG-Based Neurofeedback Game for Focus Level Enhancement 14. Detecting K-Complexes in Brain Signals Using WSST2-DETOKS 15. Directed Functional Brain Networks: Characterization of Information Flow Direction during Cognitive Function Using Non-Linear Granger Causality 16. Student Behavior Modeling and Context Acquisition: A Ubiquitous Learning Framework
1. Simulation Tools for Brain Signal Analysis 2. Processing Techniques and Analysis of Brain Sensor Data Using Electroencephalography 3. Application of Machine-Learning Techniques in Electroencephalography Signals 4. Revolution of Brain Computer Interface: An Introduction 5. Signal Modeling Using Spatial Filtering and Matching Wavelet Feature Extraction for Classification of Brain Activity Pattern 6. Study and Analysis of the Visual P300 Speller on Neurotypical Subjects 7. Effective Brain Computer Interface Based on the Adaptive-Rate Processing and Classification of Motor Imagery Tasks 8. EEG-Based BCI Systems for Neurorehabilitation Applications 9. Scalp EEG Classification Using TQWT-Entropy Features for Epileptic Seizure Detection 10. An Efficient Single-Trial Classification Approach for Devanagari Script-Based Visual P300 Speller Using Knowledge Distillation and Transfer Learning 11. Deep Learning Algorithms for Brain Image Analysis 12. Evolutionary Optimization Based Two Dimensional Elliptical FIR Filters for Skull Stripping in Brain Imaging and Disorder Detection 13. EEG-Based Neurofeedback Game for Focus Level Enhancement 14. Detecting K-Complexes in Brain Signals Using WSST2-DETOKS 15. Directed Functional Brain Networks: Characterization of Information Flow Direction during Cognitive Function Using Non-Linear Granger Causality 16. Student Behavior Modeling and Context Acquisition: A Ubiquitous Learning Framework
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