Biosignal Processing and Classification Using Computational Learning and Intelligence

Biosignal Processing and Classification Using Computational Learning and Intelligence: Principles, Algorithms and Applications posits an approach for biosignal processing and classification using computational learning and intelligence, highlighting that the term biosignal refers to all kinds of signals that can be continuously measured and monitored in living beings. The book is composed of four relevant parts. Part One is an introduction to biosignals and their processing. Part Two presents the fundamentals of computational learning (machine learning). Then, the main techniques of computational intelligence are described along with the hybrid systems, which are the resulting combinations of these techniques. The authors focus primarily on the explanation of the most used methods in the last part of this book, which is the most extensive portion of the book. This part consists of a recapitulation of the newest applications in which these techniques have been successfully applied to the biosignals' domain, including EEG-based Brain-Computer Interfaces (BCI), emotion recognition from voice, leukemia recognition, infant cry recognition, epilepsy diagnosis from EEG, and automatic smell recognition. Provides coverage of the fundamentals of signal processing, including sensing the heart, sending the brain, sensing human acoustic, and sensing other organs Includes coverage biosignal pre-processing techniques such as filtering, artifiact removal, and feature extraction techniques such as Fourier transform, wavelet transform, and MFCC Covers the latest techniques in machine learning and computational intelligence, including Supervised Learning, common classifiers, feature selection, dimensionality reduction, fuzzy logic, neural networks, Deep Learning, bio-inspired algorithms, and Hybrid Systems Written by engineers to help engineers, computer scientists, researchers, and clinicians understand the technology and applications of computational learning to biosignal processing

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  • Author : Alejandro Antonio Torres Garcia
  • Publisher : Academic Press
  • Pages : 432 pages
  • ISBN : 9780128201251
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKBiosignal Processing and Classification Using Computational Learning and Intelligence

Biosignal Processing and Classification Using Computational Learning and Intelligence

Biosignal Processing and Classification Using Computational Learning and Intelligence
  • Author : Alejandro Antonio Torres Garcia,Carlos Alberto Reyes Garcia,Luis Villasenor-Pineda,Omar Mendoza Montoya
  • Publisher : Academic Press
  • Release : 15 October 2021
GET THIS BOOKBiosignal Processing and Classification Using Computational Learning and Intelligence

Biosignal Processing and Classification Using Computational Learning and Intelligence: Principles, Algorithms and Applications posits an approach for biosignal processing and classification using computational learning and intelligence, highlighting that the term biosignal refers to all kinds of signals that can be continuously measured and monitored in living beings. The book is composed of four relevant parts. Part One is an introduction to biosignals and their processing. Part Two presents the fundamentals of computational learning (machine learning). Then, the main techniques of

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

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GET THIS BOOKMachine Learning in Bio-Signal Analysis and Diagnostic Imaging

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  • Publisher : Academic Press
  • Release : 19 August 2020
GET THIS BOOKBiomedical Signal Processing and Artificial Intelligence in Healthcare

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Biomedical Signal Processing and Artificial Intelligence in Healthcare

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  • Publisher : Academic Press
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GET THIS BOOKBiomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare is a new volume in the Developments in Biomedical Engineering and Bioelectronics series. This volume covers the basics of biomedical signal processing and artificial intelligence. It explains the role of machine learning in relation to processing biomedical signals and the applications in medicine and healthcare. The book provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of

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  • Release : 22 June 2020
GET THIS BOOKComputational Intelligence for Machine Learning and Healthcare Informatics

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GET THIS BOOKClassification and Clustering in Biomedical Signal Processing

Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research

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  • Release : 03 January 2008
GET THIS BOOKSpeech, Audio, Image and Biomedical Signal Processing using Neural Networks

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GET THIS BOOKMachine Learning and Biometrics

We are entering the era of big data, and machine learning can be used to analyze this deluge of data automatically. Machine learning has been used to solve many interesting and often difficult real-world problems, and the biometrics is one of the leading applications of machine learning. This book introduces some new techniques on biometrics and machine learning, and new proposals of using machine learning techniques for biometrics as well. This book consists of two parts: "Biometrics" and "Machine Learning

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