Brain and Behavior Computing
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Brain and Behavior Computing

Brain and Behavior Computing


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About the Book

Brain and Behavior Computing offers insights into the functions of the human brain. This book provides an emphasis on brain and behavior computing with different modalities available such as signal processing, image processing, data sciences, statistics further it includes fundamental, mathematical model, algorithms, case studies, and future research scopes. It further illustrates brain signal sources and how the brain signal can process, manipulate, and transform in different domains allowing researchers and professionals to extract information about the physiological condition of the brain. Emphasizes real challenges in brain signal processing for a variety of applications for analysis, classification, and clustering. Discusses data sciences and its applications in brain computing visualization. Covers all the most recent tools for analysing the brain and it’s working. Describes brain modeling and all possible machine learning methods and their uses. Augments the use of data mining and machine learning to brain computer interface (BCI) devices. Includes case studies and actual simulation examples. This book is aimed at researchers, professionals, and graduate students in image processing and computer vision, biomedical engineering, signal processing, and brain and behavior computing.

Table of Contents:
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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Product Details
  • ISBN-13: 9780367552992
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: CRC Press
  • Height: 234 mm
  • No of Pages: 400
  • Width: 156 mm
  • ISBN-10: 036755299X
  • Publisher Date: 25 Sep 2023
  • Binding: Paperback
  • Language: English
  • Weight: 453 gr


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