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Nonlinear biomedical signal processing. Volume 1, Fuzzy logic, neural networks, and new algorithms / edited by Metin Akay.

Contributor(s): Akay, Metin | John Wiley & Sons [publisher.] | IEEE Engineering in Medicine and Biology Society | IEEE Xplore (Online service) [distributor.].
Material type: materialTypeLabelBookSeries: IEEE Press series on biomedical engineering: 5Publisher: New York : IEEE Press, c2000Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2000]Description: 1 PDF (276 pages) : illustrations (some color).Content type: text Media type: electronic Carrier type: online resourceISBN: 9780470545362.Other title: Fuzzy logic, neural networks, and new algorithms.Subject(s): Signal processing | Biomedical engineering | Fuzzy logic | Neural networks (Computer science) | Accuracy | Adaptive filters | Algorithm design and analysis | Artificial neural networks | Biographies | Bioinformatics | Biological neural networks | Biology | Biomedical imaging | Biomedical measurements | Brain modeling | Brain models | Calibration | Classification algorithms | Clustering algorithms | Computer architecture | Electrodes | Firing | Forecasting | Function approximation | Fuzzy set theory | Fuzzy sets | Genomics | Hippocampus | History | Humans | Indexes | Interpolation | Knowledge representation | Machine learning | Mathematical model | Matrix decomposition | Minimization | Monte Carlo methods | Multilayer perceptrons | Neurons | Noise | Partitioning algorithms | Pattern recognition | Prediction algorithms | Prototypes | Radial basis function networks | Signal processing algorithms | Spectral analysis | Stomach | Sugar | Surface fitting | Time series analysis | Training | Uncertainty | Vector quantizationGenre/Form: Electronic books.Additional physical formats: Print version:: No titleDDC classification: 610/.285/632 Online resources: Abstract with links to resource Also available in print.
Contents:
Preface. List of Contributors. Uncertainty Management in Medical Applications (B. Bouchon-Meunier). Applications of Fuzzy Clustering to Biomedical Signal Processing and Dynamic System (A. Geva). Neural Networks: A Guided Tour (S. Haykin). Neural Networks in Processing and Analysis of Biomedical Signals (H. Nazeran & K. Behbehani). Rare Event Detection in Genomic Sequences by Neural Networks and Sample Stratification (W. Choe, et al.). An Axiomatic Approach to Reformulating Radial Basis Neural Networks (N. Karayiannis). Soft Learning Vector Quantization and Clustering Algorithms Based on Reformulation (N. Karayiannis). Metastable Associative Network Models of Neuronal Dynamics Transition During Sleep (M. Nakao & M. Yamamoto). Artificial Neural Networks for Spectroscopic Signal Measurement (C.-W. Lin, et al.). Applications of Feed-Forward Neural Networks in the Electrogastrogram (Z. Lin & J. Chen). Index. About the Editor.
Summary: For the first time, eleven experts in the fields of signal processing and biomedical engineering have contributed to an edition on the newest theories and applications of fuzzy logic, neural networks, and algorithms in biomedicine. Nonlinear Biomedical Signal Processing, Volume I provides comprehensive coverage of nonlinear signal processing techniques. In the last decade, theoretical developments in the concept of fuzzy logic have led to several new approaches to neural networks. This compilation delivers plenty of real-world examples for a variety of implementations and applications of nonlinear signal processing technologies to biomedical problems. Included here are discussions that combine the various structures of Kohenen, Hopfield, and multiple-layer "designer" networks with other approaches to produce hybrid systems. Comparative analysis is made of methods of genetic, back-propagation, Bayesian, and other learning algorithms. Topics covered include: . Uncertainty management. Analysis of biomedical signals. A guided tour of neural networks. Application of algorithms to EEG and heart rate variability signals. Event detection and sample stratification in genomic sequences. Applications of multivariate analysis methods to measure glucose concentration Nonlinear Biomedical Signal Processing, Volume I is a valuable reference tool for medical researchers, medical faculty and advanced graduate students as well as for practicing biomedical engineers. Nonlinear Biomedical Signal Processing, Volume I is an excellent companion to Nonlinear Biomedical Signal Processing, Volume II: Dynamic Analysis and Modeling.
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"IEEE Engineering in medicine and biology society, sponsor."

Includes bibliographical references and index.

Preface. List of Contributors. Uncertainty Management in Medical Applications (B. Bouchon-Meunier). Applications of Fuzzy Clustering to Biomedical Signal Processing and Dynamic System (A. Geva). Neural Networks: A Guided Tour (S. Haykin). Neural Networks in Processing and Analysis of Biomedical Signals (H. Nazeran & K. Behbehani). Rare Event Detection in Genomic Sequences by Neural Networks and Sample Stratification (W. Choe, et al.). An Axiomatic Approach to Reformulating Radial Basis Neural Networks (N. Karayiannis). Soft Learning Vector Quantization and Clustering Algorithms Based on Reformulation (N. Karayiannis). Metastable Associative Network Models of Neuronal Dynamics Transition During Sleep (M. Nakao & M. Yamamoto). Artificial Neural Networks for Spectroscopic Signal Measurement (C.-W. Lin, et al.). Applications of Feed-Forward Neural Networks in the Electrogastrogram (Z. Lin & J. Chen). Index. About the Editor.

Restricted to subscribers or individual electronic text purchasers.

For the first time, eleven experts in the fields of signal processing and biomedical engineering have contributed to an edition on the newest theories and applications of fuzzy logic, neural networks, and algorithms in biomedicine. Nonlinear Biomedical Signal Processing, Volume I provides comprehensive coverage of nonlinear signal processing techniques. In the last decade, theoretical developments in the concept of fuzzy logic have led to several new approaches to neural networks. This compilation delivers plenty of real-world examples for a variety of implementations and applications of nonlinear signal processing technologies to biomedical problems. Included here are discussions that combine the various structures of Kohenen, Hopfield, and multiple-layer "designer" networks with other approaches to produce hybrid systems. Comparative analysis is made of methods of genetic, back-propagation, Bayesian, and other learning algorithms. Topics covered include: . Uncertainty management. Analysis of biomedical signals. A guided tour of neural networks. Application of algorithms to EEG and heart rate variability signals. Event detection and sample stratification in genomic sequences. Applications of multivariate analysis methods to measure glucose concentration Nonlinear Biomedical Signal Processing, Volume I is a valuable reference tool for medical researchers, medical faculty and advanced graduate students as well as for practicing biomedical engineers. Nonlinear Biomedical Signal Processing, Volume I is an excellent companion to Nonlinear Biomedical Signal Processing, Volume II: Dynamic Analysis and Modeling.

Also available in print.

Mode of access: World Wide Web

Description based on PDF viewed 12/21/2015.

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