Dynamic Fuzzy Pattern Recognition with Applications to Finance and
Engineering focuses on fuzzy clustering methods which have proven to
be very powerful in pattern recognition and considers the entire process
of dynamic pattern recognition. This book sets a general framework for
Dynamic Pattern Recognition, describing in detail the monitoring process
using fuzzy tools and the adaptation process in which the classifiers
have to be adapted, using the observations of the dynamic process. It
then focuses on the problem of a changing cluster structure (new
clusters, merging of clusters, splitting of clusters and the detection
of gradual changes in the cluster structure). Finally, the book
integrates these parts into a complete algorithm for dynamic fuzzy
classifier design and classification.