Neural networks
著者
書誌事項
Neural networks
A. Waller, 1995
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注記
Updated versions of papers given at a conference under the auspices of UNICOM Seminars
Includes bibliographies and index
内容説明・目次
内容説明
Neural networks, based on simple adaptive models of living neurons, has shown itself able to tackle a very wide range of problems, particularly in conjunction with probabilistic reasoning and Bayesian belief networks using local computations. Similarly genetic algorithms and simulated annealing have been used for the solution of a large range of optimization problems. Complex tasks in areas such as machine vision, time-series analysis, robotics, control, cost analysis, and even share price and currency prediction are routinely handled by neural networks. They are also proving of importance in the development of mixed hybrid systems, which utilize other approaches to hard information processing techniques. Genetic algorithms, expert systems and Bayesian techniques are all being combined with neural network constructions to give ever-more powerful applications. Experience, can be shown to work acceptably well.
The book should be of interest to all those working in: adaptive information processing, particularly in the allied fields of computer science, electrical engineering, physics and mathematics; also those researching in the neurosciences and branches of psychology and philsophy, particularly those concerned with neural modelling should benefit from this book. Corporate users include IT specialists , production and control engineers, research and development departments, and consultants. There are two companion volumes to this book, "Probability Reasoning and Bayesian Belief Networks" and "Applications of Modern Heuristic Methods", which individually stand alone, but combined form a set treating a broad but integrated spectrum of techniques and tools for undertaking complex tasks.
目次
- The promise of neural networks
- neural network applications - some case studies
- applying neural networks in real applications
- neural computing awareness and technology transfer
- the theory and practice of N-tuple neural networks
- performing variable binding with a neural network
- neural net training - random versus systematic
- segmentation and matching in infra-red airborne images using a binary neural network
- optic, flow determination by means of a neural net
- neural networks and data visualization
- the use of neural networks for region labelling and scene understanding
- real-time control of a high-temperature plasma using a hardware neural network
- route-finding by neural nets
- a comparison of traditional methods, statistical techniques and neural networks for machine-condition monitoring
- measuring the performance of neural networks in modern portfolio management - testing strategies and metrics
- neural networks - managing innovations
- building hybrid systems with neural networks and genetic algorithms
- neuro-fuzzy high-dimensional approximation
- neuro-fuzzy networks for process modelling and fault diagnosis
- hardware-realizable neural networks
- modelling consciousness.
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