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E-raamat: Brain and Behavior Computing

Edited by (IIITB, India), Edited by (National Institute of Technology Raipur, India)
  • Formaat: 428 pages
  • Ilmumisaeg: 23-Jun-2021
  • Kirjastus: CRC Press
  • Keel: eng
  • ISBN-13: 9781000387155
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Brain and Behavior ComputingSuurem pilt
  • Formaat: 428 pages
  • Ilmumisaeg: 23-Jun-2021
  • Kirjastus: CRC Press
  • Keel: eng
  • ISBN-13: 9781000387155
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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.



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.

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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Püsilink: https://www.kriso.ee/db/97810003871552e.html
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