Journal
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume 53, Issue 11, Pages 2289-2299Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2006.881766
Keywords
classification of temporal sequences; dynamic neural networks (DNNs); optimal control; pattern recognition
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This paper reviews the application of continuous recurrent neural networks with time-varying weights to pattern recognition tasks in medicine. A general learning algorithm based on Pontryagin's maximum principle is recapitulated, and possibilities of improving the generalization capabilities of these networks are given. The effectiveness of the methods is demonstrated by three different real-world examples taken from the fields of anesthesiology, orthopedics, and radiology.
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