The revitalization of neural network research in the past few years has already had a great impact on research and development in pattern recognition and artificial intelligence.
Fuzzy sets and fuzzy logic are powerful mathematical tools for modeling and controlling uncertain systems in industry, humanity, and nature; they are facilitators for approximate reasoning in decision making in the absence of complete and precise information.
Leon Cooper's somewhat peripatetic career has resulted in work in quantum field theory, superconductivity, the quantum theory of measurement as well as the mechanisms that underly learning and memory.
This book aims to describe in simple terms the new area of statistical mechanics known as spin-glasses, encompassing systems in which quenched disorder is the dominant factor.
Recently, there has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of robot control in an "e;on-and-off"e; fashion.
Revolutionary and original, this treatise presents a new paradigm of EMERGENCE and COMPLEXITY, with applications drawn from numerous disciplines, including artificial life, biology, chemistry, computation, physics, image processing, information science, etc.
This book presents in detail the newly developed sequential learning algorithm for radial basis function neural networks, which realizes a minimal network.
Recent developments in the neurosciences have considerably modified our knowledge of both the operating modes of neurons and information processing in the cortex.
In order to develop new types of information media and technology, it is essential to model complex and flexible information processing in living systems.
Neural networks are increasingly being used in real-world business applications and, in some cases, such as fraud detection, they have already become the method of choice.
This book presents worldwide outstanding research and recent progress in the applications of neural networks, fuzzy logic, chaos, independent component analysis, etc to fields related to speech recognition enhancement, supervised Fourier demixing noise elimination, acoustic databases, the human hearing system, cancer detection, image processing, and visual communications.
Soft computing (SC) consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as genetic algorithms.
Soft computing has been presented not only with the theoretical developments but also with a large variety of realistic applications to consumer products and industrial systems.
This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking.
This book consists of various contributions in conjunction with the keywords "e;reasoning"e; and "e;intelligent systems"e;, which widely covers theoretical to practical aspects of intelligent systems.
Connectionist Models of Cognition and Perception collects together refereed versions of twenty-three papers presented at the Seventh Neural Computation and Psychology Workshop (NCPW7).
Cellular computing is a natural information processing paradigm, capable of modeling various biological, physical and social phenomena, as well as other kinds of complex adaptive systems.
The Pacific Symposium on Biocomputing (PSB 2003) is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance.
This book provides a thorough theoretical and practical introduction to the application of neural networks to pattern recognition and intelligent signal processing.
The Pacific Symposium on Biocomputing (PSB 2004) is an international, multidisciplinary conference for the presentation and discussion of current research on the theory and application of computational methods in problems of biological significance.
In recent years, complex-valued neural networks have widened the scope of application in optoelectronics, imaging, remote sensing, quantum neural devices and systems, spatiotemporal analysis of physiological neural systems, and artificial neural information processing.
For engineering applications that are based on nonlinear phenomena, novel information processing systems require new methodologies and design principles.
The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments.