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.
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