This concise but comprehensive textbook reviews the most popular
neural-network methods and their associated techniques. Each
chapter provides state-of-the-art descriptions of important major
research results of the respective neural-network methods. A range
of relevant computational intelligence topics, such as fuzzy logic
and evolutionary algorithms - powerful tools for neural-network
learning - are introduced. The systematic survey of neural-network
models and exhaustive references list will point readers toward
topics for future research. The algorithms outlined also make this
textbook a valuable reference for scientists and practitioners
working in pattern recognition, signal processing, speech and image
processing, data analysis and artificial intelligence.
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