Pattern Formation By Dynamic Systems And Pattern Recognition

This book contains the manuscripts of the papers delivered at the International Sym posium on Synergetics held at SchloB Elmau, Bavaria, Germany, from April 30 until May 5, 1979. This conference followed several previous ones (Elmau 1972, Sicily 1974, Elmau 1977). This time the subject of the symposium was "pattern formation by dynam ic systems and pattern recognition". The meeting brought together scientists from such diverse fields as mathematics, physics, chemistry, biology, history as well as experts in the fields of pattern recognition and associative memory. When I started this type of conference in 1972 it appeared to be a daring enter prise. Indeed, we began to explore virgin land of science: the systematic study of cooperative effects in physical systems far from equi~ibrium and in other disciplines. Though these meetings were attended by scientists from quite different disciplines, a basic concept and even a common language were found from the very beginning. The idea that there exist profound analogies in the behaviour of large classes of complex systems, though the systems themselves may be quite different, proved to be most fruitful. I was delighted to see that over the past one or two years quite similar conferences were now held in various places allover the world. The inclusion of prob lems of pattern recognition at the present meeting is a novel feature, however.

Handbook of Optimization in Medicine is devoted to examining the dramatic increase in the application of effective optimization techniques to the delivery of health care. The articles, written by experts, focus on models and algorithms that have led to more efficient and sophisticated treatments of patients. Topics covered include: optimization in medical imaging, classification and data mining with medical applications, treatment of epilepsy and other brain disorders, treatment of head-and-neck, prostate, and other cancers using conventional conformal and intensity-modulated radiation therapy as well as proton therapy, treatment selection for breast cancer based on new classification schemes, optimization for the genome project, optimal timing of organ transplants.

This is the second volume in a series intended to give clear expositions of the applications of the new techniques developed to understand nonlinear phenomena in the life sciences. The first paper by West, Mackey and Chen is methodological in nature and reviews how to distinguish between noise in biomedical data sets and irregularities generated by deterministic dynamical equations. The second paper by Hock, Sch”ner, Balz, Eastman and Voss addresses the problem of pattern formation and pattern change in the vision system. The authors emphasize the experimental correspondence between quantifiable perceptual phenomena and certain features of nonlinear dynamical systems theory.The paper by Chay focuses on modeling strategies for biological phenomena that manifest strong nonlinear behavior. Biological rhythms and electrical bursting phenomena are discussed in detail, and certain apparently random processes are shown to be describable by chaos. The final paper is an attempt by Nicolis and Katsikas to use nonlinear dynamics systems theory to develop a general theory of linguistics. The concepts of information and pattern recognition are used in concert with that of a dynamic attractor to argue for the general properties of a cognitive processor.

Neural and Synergetic Computers deals with basic aspect of this rapidly developing field. Several contributions are devoted to the application of basic concepts of synergetics and dynamic systems theory to the constructionof neural computers. Further topics include statistical approaches to neural computers and their design (for example by sparse coding), perception motor control, and new types of spatial multistability in lasers.

During the past two decades there has been a considerable growth in interest in problems of pattern recognition and image processing (PRIP). This inter est has created an increasing need for methods and techniques for the design of PRIP systems. PRIP involves analysis, classification and interpretation of data. Practical applications of PRIP include character recognition, re mote sensing, analysis of medical signals and images, fingerprint and face identification, target recognition and speech understanding. One difficulty in making PRIP systems practically feasible, and hence, more popularly used, is the requirement of computer time and storage. This situation is particularly serious when the patterns to be analyzed are quite complex. Thus it is of the utmost importance to investigate special comput er architectures and their implementations for PRIP. Since the advent of VLSI technology, it is possible to put thousands of components on one chip. This reduces the cost of processors and increases the processing speed. VLSI algorithms and their implementations have been recently developed for PRIP. This book is intended to document the recent major progress in VLSI system design for PRIP applications.