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Neural Networks - An Introduction

by Berndt Muller, Joachim Reinhardt e Michael T. Strickland

59,61€ + 10% CARD

 The concepts of neural-network models and techniques of parallel distributed processing are presented in this volume in an approach which includes a brief overview of the neural structure of the brain and the history of neural-network modelling.
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Models Of Neural Networks I

59,61€ + 10% CARD

 This text begins with an introduction to the ideas used in the subsequent chapters, which are all centred around the theme of collective phenomena in neural networks. These include dynamics and storage capacity of networks of formal neurons with symmetric or asymmetric couplings.
ENGLISH

Models Of Neural Networks

95,40€ + 10% CARD

 One of the great inteJlectual cha1lenges for the next few decades is the question of brain organization. What is the basic mechanism for storage of memory? What are the processes that serve as the interphase between the basically chemical processes of the body and the very specific and nonstatistical operations in the brain? Above all. how is concept formation achieved in the human brain? I wonder whether the spirit of the physics that will be involved in these studies will not be akin to that which moved the founders of the ''''rational foundation of thermodynamics". CN. Yangl 10 The human brain is said 10 have roughly 10 neurons connected through about 14 10 synapses. Each neuron is itself a complex device which compares and integrates incoming electrical signals and relays a nonlinear response to other neurons. The brain certainly exceeds in complexity any system which physicists have studied in the past. Nevertheless, there do exist many analogies of the We have witnessed during the last decade brain to simpler physical systems.
ENGLISH

Neural Networks - An Introduction

by Berndt Muller e Joachim Reinhardt

56,96€ + 10% CARD

 The mysteries of the human mind have fascinated scientists and philosophers alike for centuries. Descartes identified our ability to think as the foundation stone of ontological philosophy. Others have taken the human mind as evidence of the existence of supernatural powers, or even of God. Serious scientific in vestigation, which began about half a century ago, has partially answered some of the simpler questions (such as how the brain processes visual information), but has barely touched upon the deeper ones concerned with the nature of consciousness and the possible existence of mental features transcending the biological substance of the brain, often encapsulated in the concept "soul". Besides the physiological and philosophical approaches to these questions, so impressively presented and contrasted in the recent book by Popper and Ec cles [P077), studies of formal networks composed of binary-valued information processing units, highly abstracted versions of biological neurons, either by mathematical analysis or by computer simulation, have emerged as a third route towards a better understanding of the brain, and possibly of the human mind. Long remaining - with the exception of a brief period in the early 1960s - a rather obscure research interest of a small group of dedicated scientists scattered around the world, neural-network research has recently sprung into the limelight as a "fashionable" research field.
ENGLISH

Models Of Neural Networks Iii - Association, Generalization, And Representation

118,59€ + 10% CARD

 One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, "Global Analysis of Recurrent Neural Net- works," by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. It includes a review of the recent work with John Hopfield on integrate-and- fire neurons with local interactions. The chapter, "Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns" by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu- ment since has been shown to be rather susceptible to generalization.
ENGLISH

Models Of Neural Networks Iv - Early Vision And Attention

59,61€ + 10% CARD

 Close this book for a moment and look around you. You scan the scene by directing your attention, and gaze, at certain specific objects. Despite the background, you discern them. The process is partially intentional and partially preattentive. How all this can be done is described in the fourth volume of Models of Neural Networks devoted to Early Vision and Atten tion that you are holding in your hands. Early vision comprises the first stages of visual information processing. It is as such a scientific challenge whose clarification calls for a penetrating review. Here you see the result. The Heraeus Foundation (Hanau) is to be thanked for its support during the initial phase of this project. John Hertz, who has extensive experience in both computational and ex perimental neuroscience, provides in "Neurons, Networks, and Cognition" to neural modeling. John Van Opstal explains in a theoretical introduction "The Gaze Control System" how the eye's gaze control is performed and presents a novel theoretical description incorporating recent experimental results. We then turn to the relay stations thereafter, the lateral genicu late nucleus (LGN) and the primary visual cortex. Their anatomy, phys iology, functional relations, and ensuing response properties are carefully analyzed by Klaus Funke et al. in "Integrating Anatomy and Physiology of the Primary Visual Pathway: From LGN to Cortex", one of the most comprehensive reviews that is available at the moment.
ENGLISH

Models Of Neural Networks - Temporal Aspects Of Coding And Information Processing In Biological Systems

171,59€ + 10% CARD

 Provides an in-depth analysis of both paradigms starting with an introduction to the ideas used in the subsequent chapters. In this book, one finds a discussion of salient features such as coherent oscillations and their detection, associative binding and segregation, Hebbian learning, and sensory computations in the visual and olfactory cortex.

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