Biological signals classification and analysis
type: Item
instance of: scholarly article
title: Biological signals classification and analysis
zbMATH Open document ID: 1330.92002
DOI: 10.1007/978-3-642-54879-6
author: Kamran Kiasaleh
published in: Lecture Notes in Bioengineering
publication date: 2015-08-04T00:00:00Z
review text: The book offers a comprehensive yet well focused exposition of the classification and analysis of biological signals. Those signals, being generated by humans, create a genuine challenge given their inherent nonlinearity and/or chaotic character, non-stationarity, and the existence of various sources of noises. These challenges are well emphasized and reflected in the content and an overall organization of the volume. The book, divided into six chapters, is well structured and the exposition is clear and carefully thought-out. Three main parts can be distinguished, each of them coming with a well-defined objective. The first part, composed of two chapters, focuses on the background material about signals and linear and nonlinear models, including topics such as deterministic and stochastic signals. Particular attention is paid to the description of properties and operations on signals (sampling, quantization, stationarity, spectrum, response analysis). Biological signals, presented in Chapter 3, concern three categories of signals, namely, ECG, EEG, and EMG. These signals are discussed in depth and their underlying origin and main characteristics are well covered. Chapters 4 and 5 are devoted to selected methods of signal processing of biological signals. Chapter 4 focuses on the description of signals (viz., independence, Gaussian characterization, orthogonality). Several ways of computing distance between probability density functions (Kolgomogorov-Smirnov, Hellinger, etc.) along with the detection and estimation methods are presented as well. Chapter 5 is about decomposition methods and covers principle component analysis and wavelet decomposition. Chapter 6 delivers some conclusions and a list of references. The carefully selected illustrative material, a great deal of figures, solved examples, and the clear interpretations of results offer a tangible didactic value of the book. While the exposition of the material is coherent, it could have been desirable to ha…
reviewed by: Witold Pedrycz
Mathematics Subject Classification ID: 92-01
Mathematics Subject Classification ID: 92C55
Mathematics Subject Classification ID: 92C42
Mathematics Subject Classification ID: 65T60
zbMATH DE Number: 6469886
zbMATH Keywords: biological signals
zbMATH Keywords: noises
zbMATH Keywords: sampling
zbMATH Keywords: quantization
zbMATH Keywords: spectrum
zbMATH Keywords: response analysis
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1007/978-3-642-54879-6
OpenAlex ID: W2344943445
description: scientific article