Brain and Behavior Computing (eBook, PDF)

Redaktion: Sahu, Mridu; Sinha, G R

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 428
• Erscheinungstermin: 23. Juni 2021
• Englisch
• ISBN-13: 9781000387155
• Artikelnr.: 61781611

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