The systematic scientific investigation of human perception began over 130 years ago, yet relatively little is known about how we identify complex patterns. A major reason for this is that historically, most perceptual research focused on the more basic processes involved in the detection and discrimination of simple stimuli. This work progressed in a connectionist fashion, attempting to clarify fundamental mechanisms in depth before addressing the more complex problems of pattern recognition and classification. This extensive and impressive research effort built a firm basis from which to speculate about these issues. What seemed lacking, however, was an overall characterization of the recognition problem – a broad theoretical structure to direct future research in this area. Consequently, our primary objective in this volume, originally published in 1981, was not only to review existing contributions to our understanding of classification and recognition, but to project fruitful areas and directions for future research as well. The book covers four areas: complex visual patterns; complex auditory patterns; multi-dimensional perceptual spaces; theoretical pattern recognition.

The systematic scientific investigation of human perception began over 130 years ago, yet relatively little is known about how we identify complex patterns. A major reason for this is that historically, most perceptual research focused on the more basic processes involved in the detection and discrimination of simple stimuli. This work progressed in a connectionist fashion, attempting to clarify fundamental mechanisms in depth before addressing the more complex problems of pattern recognition and classification. This extensive and impressive research effort built a firm basis from which to speculate about these issues. What seemed lacking, however, was an overall characterization of the recognition problem – a broad theoretical structure to direct future research in this area. Consequently, our primary objective in this volume, originally published in 1981, was not only to review existing contributions to our understanding of classification and recognition, but to project fruitful areas and directions for future research as well. The book covers four areas: complex visual patterns; complex auditory patterns; multi-dimensional perceptual spaces; theoretical pattern recognition.

The human brain, wi th its hundred billion or more neurons, is both one of the most complex systems known to man and one of the most important. The last decade has seen an explosion of experimental research on the brain, but little theory of neural networks beyond the study of electrical properties of membranes and small neural circuits. Nonetheless, a number of workers in Japan, the United States and elsewhere have begun to contribute to a theory which provides techniques of mathematical analysis and computer simulation to explore properties of neural systems containing immense numbers of neurons. Recently, it has been gradually recognized that rather independent studies of the dynamics of pattern recognition, pattern format::ion, motor control, self-organization, etc. , in neural systems do in fact make use of common methods. We find that a "competition and cooperation" type of interaction plays a fundamental role in parallel information processing in the brain. The present volume brings together 23 papers presented at a U. S. -Japan Joint Seminar on "Competition and Cooperation in Neural Nets" which was designed to catalyze better integration of theory and experiment in these areas. It was held in Kyoto, Japan, February 15-19, 1982, under the joint sponsorship of the U. S. National Science Foundation and the Japan Society for the Promotion of Science. Participants included brain theorists, neurophysiologists, mathematicians, computer scientists, and physicists. There are seven papers from the U. S.

Methodologies of Pattern Recognition is a collection of papers that deals with the two approaches to pattern recognition (geometrical and structural), the Robbins-Monro procedures, and the implications of interactive graphic computers for pattern recognition methodology. Some papers describe non-supervised learning in statistical pattern recognition, parallel computation in pattern recognition, and statistical analysis as a tool to make patterns emerge from data. One paper points out the importance of cluster processing in visual perception in which proximate points of similar brightness values form clusters. At higher levels of mental activity humans are efficient in clumping complex items into clusters. Another paper suggests a recognition method which combines versatility and an efficient noise-proofness in dealing with the two main problems in the field of recognition. These difficulties are the presence of a large variety of observed signals and the presence of interference. One paper reports on a possible feature selection for pattern recognition systems employing the minimization of population entropy. Electronic engineers, physicists, physiologists, psychologists, logicians, mathematicians, and philosophers will find great rewards in reading the above collection.

First published in 1979. Basic research, at its essence, is exploration of the unknown. When it is successful, isolated pieces of reality are deciphered and described. Most of the history of an empirical discipline consists of probes into this darkness-some bold, others careful and systematic. Most of these efforts are initially incorrect. At best, they are distant approximations to a reality that may not be correctly specified for centuries. How, then, can we describe the fragmented knowledge that characterizes a scientific discipline for most of its history? A dynamic field of science is held together by its paradigm. The author’s think it is essential to adequate scientific education to teach paradigms, and believe that there is an effective method. The method emphasizes the integral nature, rather than the objective correctness, of a given set of consensual commitments. They believe that paradigmatic content can be effectively combined with the technical research literature commonly presented in scientific texts. This book represents the culmination of those beliefs.

This unique sourcebook describes the research methods used to study human brain function and brain-behavior relationships. These range from relatively simple approaches, such as dichotic listening and tachistoscopic presentation, to computerized techniques such as cerebral blood flow measurements. The description of each method covers the underlying theory, variations on the basic paradigm, dependent measures, reliability and validity, and the equipment required. The authors also critically review research with normal and clinical populations. Because of the rapid expansion of the field of human neuropsychology--and accompanying technological advances--this volume will be valued as much by experienced researchers as by newcomers seeking an introduction to the variety of available procedures.

This book constitutes the refereed proceedings of the 25th Symposium of the German Association for Pattern Recognition, DAGM 2003, held in Magdeburg, Germany in September 2003. The 74 revised papers presented were carefully reviewed and selected from more than 140 submissions. The papers address all current issues in pattern recognition and are organized in sections on image analyses, callibration and 3D shape, recognition, motion, biomedical applications, and applications.