• 1 Introduction.- 2 General Framework of Dynamic Pattern Recognition.- 3 Stages of the Dynamic Pattern Recognition Process.- 4 Dynamic Fuzzy Classifier Design with Point-Prototype Based Clustering Algorithms.- 5 Similarity Concepts for Dynamic Objects in Pattern Recognition.- 6 Applications of Dynamic Pattern Recognition Methods.- 7 Conclusions.- References.- Unsupervised Optimal Fuzzy Clustering Algorithm of Gath and Geva.- Description of Implemented Software.

'The book could be considered as a lucid, clear and well to read theoretical treatise about fuzzy dynamic pattern recognition. It is particularly commendable that Dr. Angstenberger does not stop here, but that she shows very clearly how her suggestions really work in applications. In my view this book really presents a breakthrough in a new area of pattern recognition. It will certainly be the basis for many other research projects and real applications. I can only congratulate her to this excellent scientific and application oriented work and hope that it may be of benefit to many scientists and practitioners.' From the foreword by H.-J. Zimmermann, Aachen, Germany, January 2001