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.
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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