Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing
eBook - ePub

Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing

  1. 226 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing

About this book

The book provides details regarding the application of various signal processing and artificial intelligence-based methods for electroencephalography data analysis. It will help readers in understanding the use of electroencephalography signals for different neural information processing and cognitive neuroscience applications. The book:

  • Covers topics related to the application of signal processing and machine learning-based techniques for the analysis and classification of electroencephalography signals
  • Presents automated methods for detection of neurological disorders and other applications such as cognitive task recognition, and brain-computer interface
  • Highlights the latest machine learning and deep learning methods for neural signal processing
  • Discusses mathematical details for the signal processing and machine learning algorithms applied for electroencephalography data analysis
  • Showcases the detection of dementia from electroencephalography signals using signal processing and machine learning-based techniques

It is primarily written for senior undergraduates, graduate students, and researchers in the fields of electrical engineering, electronics and communications engineering, and biomedical engineering.

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Yes, you can access Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing by Rajesh Kumar Tripathy,Ram Bilas Pachori in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Computer Engineering. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title
  4. Copyright
  5. Contents
  6. Preface
  7. Editor Biographies
  8. List of Contributors
  9. Chapter 1 Introduction to EEG Signal Recording and Processing
  10. Chapter 2 Artificial Intelligence-Enabled EEG Signal Processing-Based Detection of Epileptic Seizures
  11. Chapter 3 Classification of Normal and Alcoholic EEG Signals Using Signal Processing and Machine Learning
  12. Chapter 4 Empirical Wavelet Transform and Gradient Boosted Learners for Automated Classification of Epileptic Seizures from EEG Signals
  13. Chapter 5 Automated Emotion Recognition from EEG Signals Using Machine Learning Algorithms in the Field of Ambient Assisted Living
  14. Chapter 6 Automated Recognition of Human Emotions from EEG Signals Using Signal Processing and Machine Learning Techniques
  15. Chapter 7 Automatic Emotion Detection by EEG Analysis Using Graph Signal Processing
  16. Chapter 8 Automated Detection of Alzheimer’s Disease Using EEG Signal Processing and Machine Learning
  17. Chapter 9 A Regularized Riemannian Intelligent System for Dementia Screening Using Magnetoencephalography Signals
  18. Chapter 10 Detecting Dementia Using EEG Signal Processing and Machine Learning
  19. Chapter 11 EEG Signal Processing-Driven Machine Learning for Cognitive Task Recognition
  20. Chapter 12 Detection of Stress Levels During the Stroop Color-Word Test Using Multivariate Projection-Based MUSIC Domain EWT of Multichannel EEG Signal and Machine Learning
  21. Index