Description

Book Synopsis

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 poss

    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

Brain and Behavior Computing

    Product form

    £120.00

    Includes FREE delivery

    Order before 4pm today for delivery by Mon 8 Jun 2026.

    A Hardback by Mridu Sahu, G R Sinha

    1 in stock


      View other formats and editions of Brain and Behavior Computing by Mridu Sahu

      Publisher: CRC Press
      Publication Date: 6/24/2021 12:00:00 AM
      ISBN13: 9780367552978, 978-0367552978
      ISBN10: 0367552973

      Description

      Book Synopsis

      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 poss

        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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