This monograph describes new methods for intelligent pattern
recognition using soft computing techniques including neural
networks, fuzzy logic, and genetic algorithms. Hybrid intelligent
systems that combine several soft computing techniques are needed
due to the complexity of pattern recognition problems. Hybrid
intelligent systems can have different architectures, which have an
impact on the efficiency and accuracy of pattern recognition
systems, to achieve the ultimate goal of pattern recognition. This
book also shows results of the application of hybrid intelligent
systems to real-world problems of face, fingerprint, and voice
recognition. This monograph is intended to be a major reference for
scientists and engineers applying new computational and
mathematical tools to intelligent pattern recognition and can be
also used as a textbook for graduate courses in soft computing,
intelligent pattern recognition, computer vision, or applied
artificial intelligence.
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