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Pattern Recognition
On External Measures for Validation of Fuzzy Partitions
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
Applied Soft Computing
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Optimal feature selection for the assessment of vocal fold disorders
Computers in Biology and Medicine
Comparative clustering analysis of bispectral index series of brain activity
Expert Systems with Applications: An International Journal
Quantitative estimation of the nonstationary behavior of neural spontaneous activity
Computational Intelligence and Neuroscience - Special issue on signal processing for neural spike trains
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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From the Publisher:Biomedical / Electrical Engineering Nonlinear Biomedical Signal Processing Volume I: Fuzzy Logic, Neural Networks, and New Algorithms A volume in the IEEE Press Series on Biomedical Engineering Metin Akay, Series Editor 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 concentrationNonlinear Biomedical Signal Processing, Volume I is a valuable reference tool for medical researchers, medical faculty and advanced graduate student, s as well as for practicing biomedicalengineers. Nonlinear Biomedical Signal Processing, Volume I is an excellent companion to Nonlinear Biomedical Signal Processing, Volume II: Dynamic Analysis and Modeling.