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An Introduction to Information Processing provides an informal introduction to the computer field. This book introduces computer hardware, which is the actual computing equipment. Organized into three parts encompassing 12 chapters, this book begins with an overview of the evolution of personal computing and includes detailed case studies on two of the most essential personal computers for the 1980s, namely, the IBM Personal Computer and Apple's Macintosh. This text then traces the evolution of modern computing systems from the earliest mechanical calculating devices to microchips. Other chapters consider the components and operation of typical data communications systems. This book discusses as well the various types of communications networks and communications via space satellites. The final chapter deals with software or computer programs, the sets of instructions that programmers write to inform the computer how to solve particular problems. This book is a valuable resource for computer specialists, mathematicians, and computer programmers.
Human Information Processing: An Introduction to Psychology, Second Edition, was written to reflect recent developments, as well as anticipate new directions, in this flourishing field. The ideas of human information processing are relevant to all human activities, most especially those of human interactions. The book discusses all the traditional areas and then goes beyond: consciousness, states of awareness, multiple levels of processing (and of awareness), interpersonal communication, emotion, and stress. The book begins with an introduction to some of the more interesting phenomena of perception and poses some of the puzzles faced by those who would attempt to unravel the structures. Separate chapters cover the systems of most interest for human communication: the visual system and the auditory system; the structure of the nervous system; and the systems of memory: sensory information storage, short-term memory, and long-term memory. Subsequent chapters deal with the different aspects of memory, including show how memory is used in thought, in language, and in decision making. Also examined are the neurological basis of memory and the representation of knowledge within memory.
Proceedings of the 2002 Neural Information Processing Systems Conference.
Originally published in 1976, the authors present a theory of cognitive development based upon an information-processing approach. Here is one of the first attempts to apply the information-processing view of cognitive psychology to developmental issues raised by empirical work in the Piagetian tradition.
This new edition of a well-received textbook provides a concise introduction to both the theoretical and experimental aspects of quantum information at the graduate level. While the previous edition focused on theory, the book now incorporates discussions of experimental platforms. Several chapters on experimental implementations of quantum information protocols have been added: implementations using neutral atoms, trapped ions, optics, and solidstate systems are each presented in its own chapter. Previous chapters on entanglement, quantum measurements, quantum dynamics, quantum cryptography, and quantum algorithms have been thoroughly updated, and new additions include chapters on the stabilizer formalism and the Gottesman-Knill theorem as well as aspects of classical and quantum information theory. To facilitate learning, each chapter starts with a clear motivation to the topic and closes with exercises and a recommended reading list. Quantum Information Processing: Theory and Implementation will be essential to graduate students studying quantum information as well as and researchers in other areas of physics who wish to gain knowledge in the field.
Papers presented at NIPS, the flagship meeting on neural computation, held in December 2004 in Vancouver.The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees--physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December, 2004 conference, held in Vancouver.
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.
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 book brings together the biology and computational features of the basal ganglia and their related cortical areas along with select examples of how this knowledge can be integrated into neural network models. Recent years have seen a remarkable expansion of knowledge about the anatomical organization of the part of the brain known as the basal ganglia, the signal processing that occurs in these structures, and the many relations both to molecular mechanisms and to cognitive functions. This book brings together the biology and computational features of the basal ganglia and their related cortical areas along with select examples of how this knowledge can be integrated into neural network models. Organized in four parts - fundamentals, motor functions and working memories, reward mechanisms, and cognitive and memory operations - the chapters present a unique admixture of theory, cognitive psychology, anatomy, and both cellular- and systems- level physiology written by experts in each of these areas. The editors have provided commentaries as a helpful guide to each part. Many new discoveries about the biology of the basal ganglia are summarized, and their impact on the computational role of the forebrain in the planning and control of complex motor behaviors discussed. The various findings point toward an unexpected role for the basal ganglia in the contextual analysis of the environment and in the adaptive use of this information for the planning and execution of intelligent behaviors. Parallels are explored between these findings and new connectionist approaches to difficult control problems in robotics and engineering. Contributors James L. Adams, P. Apicella, Michael Arbib, Dana H. Ballard, Andrew G. Barto, J. Brian Burns, Christopher I. Connolly, Peter F. Dominey, Richard P. Dum, John Gabrieli, M. Garcia-Munoz, Patricia S. Goldman-Rakic, Ann M. Graybiel, P. M. Groves, Mary M. Hayhoe, J. R. Hollerman, George Houghton, James C. Houk, Stephen Jackson, Minoru Kimura, A. B. Kirillov, Rolf Kotter, J. C. Linder, T. Ljungberg, M. S. Manley, M. E. Martone, J. Mirenowicz, C. D. Myre, Jeff Pelz, Nathalie Picard, R. Romo, S. F. Sawyer, E Scarnat, Wolfram Schultz, Peter L. Strick, Charles J. Wilson, Jeff Wickens, Donald J. Woodward, S. J. Young
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.