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检索条件"任意字段=IEE Colloquium on Advances in Neural Networks for Control and Systems"

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Artificial neural networks and their application in process engineering

Artificial neural networks and their application in process ...

引用

iee colloquium on neural networks for systems: Principles and Applications

作者： M.J. Willis G.A. Montague C. Di Massimo A.J. Morris M.T. Tham Department of Chemical and Process Engineering University of Newcastle Newcastle-upon-Tyne UK Dept. of Chem. & Process Eng. Newcastle-upon-Tyne Univ. UK

A typical neural network topology consists of highly interconnected 'neuron' like nodes. These nodes act as nonlinear processing elements, hence the attractive feature of the technique is that given an appropriate network topology, nonlinear functional relationships can be characterised. Thus, the methodology provides a generic, cost effective, nonlinear modelling philosophy which may be a valuable tool in alleviating current process engineering problems. This contribution introduces the concepts involved in the formulation of artificial neural networks. Their suitability for solving process engineering problems is discussed and illustrated using results from simulation studies and applications to industrial data.< >

关键词： Circuit topology neural networks Process control

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Investigation of non-algorithmic software in flight control

Investigation of non-algorithmic software in flight control

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iee colloquium on Expert systems and Safety

作者： P.D. Houghton FS3 Division Royal Aerospace Establishment Bedford UK

Current implementations of aircraft flight control systems are an amalgam of numerous, discrete algorithms and various switching mechanisms. The switching mechanisms bring the algorithms into play either independently or in some form of combination. Advanced computing techniques, such as expert systems, can play a role by separating out the algorithm scheduling and making it more visible. By lessening the complexity both the integrity and capability should be improved. An alternative and more controversial approach is to use adaptive, learning and optimisation techniques such as neural networks. These offer advantages by removing the need for algorithm creation through learning, provide graceful degradation when elements fail and can adapt to subsystem failures. However at present this approach is not welcomed as conventional verification and validation techniques cannot be employed. The author discusses the role of non-algorithmic software.< >

关键词： Expert systems neural networks

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Structural generalization in neural classification: incorporation of prior probabilities

Structural generalization in neural classification: incorpor...

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iee colloquium on Adaptive Filtering, Non-Linear Dynamics and neural networks

作者： D.W. McMichael Control Systems Centre University of Manchester Institute of Science and Technology Manchester UK

Supervised learning of classifications under l/sub 2/ costing of error trains learning classifiers to recall Bayesian a posteriori probabilities of the possible classes, given observed measurements. This result leads to a number of insights concerning the validation of training, access to the likelihood function, creating networks of networks, incorporation of prior probabilities (which may vary in real-time), and how to choose the training set. The author focuses on the latter two points. Contextual information in the form of priors is used to generalise training data to economise on both training and computation. Structural generalization is the process whereby data is generalised architecturally rather than parametrically. A training procedure and postprocessing technique are given which enable learning under one set of prior classification probabilities to be generalized to give (asymptotically) Bayes optimal classifications under all others.< >

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Design of a VLSI-based artificial neural network system by a student group

Design of a VLSI-based artificial neural network system by a...

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iee colloquium on Eurochip Project - VLSI Design in Higher Education

作者： T. Hui J. Wilkes P. Morgan H. Bolouri K. Gurney Div. of Electr. & Electron. Eng. Hatfield Polytech. UK Division of Electrical and Electronic Engineering Hatfield Polytechnic Hatfield UK Department of Human Sciences Brunei University UK

Describes the subject of a particular group of projects carried out by undergraduate, MSc and PhD students, over the past three years. The projects relate to the analysis, design, development and construction of a VLSI-based artificial neural network (ANN) system. The projects have been carefully specified so that they complement each other without significant overlap. In general, the projects fall into one of three categories: applications development (e.g. speech recognition, image recognition, robot control), systems analysis (e.g. hardware configuration requirements for optimum system performance), and hardware design and development (e.g. design of a VLSI IC, design of a demonstrator system for the IC, design of input/output instrumentation such as CCD imagers or robot motion control components). As well as providing for a range of skill/ability levels from construction to open ended research, the projects enable students to concentrate on specific subject areas ranging from software engineering (applications) through hardware/software (systems analysis) to hardware design at IC, PCB and system levels.< >

关键词： Design automation Education neural networks Very-large-scale integration

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Real time reinforcement learning control of dynamic systems applied to an inverted pendulum

Real time reinforcement learning control of dynamic systems ...

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iee colloquium on Symbols Versus Neurons

作者： W. van Luenen Systems and Computer EngineeringGroup (BSC) Department of Electrical Engineering University of Twente Enschede Netherlands

Describes work started in order to investigate the use of neural networks for application in adaptive or learning control systems. neural networks have learning capabilities and they can be used to realize non-linear mappings. These are attractive features which could make them useful building blocks for non-linear adaptive or learning controllers.< >

关键词： Adaptive systems Learning systems neural networks

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Application of neural computing techniques to learning support environments

Application of neural computing techniques to learning suppo...

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iee colloquium on neural Nets in Human-Computer Interaction

作者： L.J. Allinson N.M. Allinson Department of Psychology University of York York UK Department of Electronics University of York York UK

The application of neural network methods is demonstrated for the analysis of data obtained in a study of a hypertext system employed in computer assisted learning (CAL). The authors also discuss the future role of ne... 详细信息

关键词： Computer aided instruction Hypertext systems neural networks

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Using the genetic algorithm to adapt intelligent systems

Using the genetic algorithm to adapt intelligent systems

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iee colloquium on Symbols Versus Neurons

作者： T.C. Fogarty Transputer Centre Bristol Polytechnic UK

The genetic algorithm, loosely based on the mechanics of evolution, is used in machine learning and optimisation problems that typically have a large search space and require a high tolerance to noise. Two examples are given of its use in the learning of rules for real-time control problems; one for adaptive rule-based optimisation of combustion in multiple-burner installations in the steel industry and the other for controlling a dynamical system. Current research on genetic algorithms is largely focussing on their use for optimising neural networks, since this is a natural way of combining the paradigms of evolution and learning, and on parallel and distributed implementations, to facilitate the efficient solution of larger problems. A project using a parallel implementation of an incremental genetic algorithm to generate constraint networks from raw data is described.< >

关键词： Digital control Genetic algorithms Learning systems neural networks Optimization methods Real time systems

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Cybernetic roots and futures of neural computing

Cybernetic roots and futures of neural computing

引用

iee colloquium on Cybernetics Today

作者： I. Aleksander Department Electronic and Electrical Engineering King's College London Technology and Medicine UK

Superficially, neural computing is intricately concerned with control and information in man and machine. However, looked at in greater depth, it seems important to keep brain studies at arms length from the making of neural computers. In fact, one could argue, neural computing could lead to a situation which is almost contrary to the aspirations of early cyberneticists. There is a danger in bringing the study of brains and machines under the same theoretical roof from the point of view that one underscores the deficiencies of brains and starts building them into machinery. In this context the author raises and answers several questions: Does close modelling of the neuron lead to the best design of machines. Does the analogue nature of neurons have to be achieved in silicon? and neurons have very large fan-in and implementations of the McCulloch and Pitts model would become very expensive if this were mimicked. Does this mean that neural computing can never aspire to human competence? The author aims to show that while constructive inputs from brain studies will always help in the effort of designing neural computers, the neural systems designer is advised to concentrate on inventing analytic tools that help him to understand the artificial world without using applicability to brain studies as a yardstick.< >

关键词： Cybernetics neural networks

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AI research issues in chemical and biochemical process engineering

AI research issues in chemical and biochemical process engin...

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iee colloquium on Strategic Research Issues in AI in Engineering

作者： A.J. Morris G.A. Montague M. Aynsley D. Peel Department of Chemical and Process Engineering University of Newcastle Newcastle-upon-Tyne UK

Rule-based expert type systems have probably run their course of academic interest and development. Richer forms of knowledge representation such as qualitative models, detailed quantitative models, pattern classification based models, order-of-magnitude relationships, etc. can be handled efficiently using modern techniques. These will provide for a real approach towards the emulation of human reasoning. AI methodologies will become ever more important as process engineers are faced with the design and operation of increasingly complex processes. This is particularly the case in process biotechnology, in metabolic pathway synthesis and in molecule and gene design. The promises of artificial intelligence methodologies, towards the solution of engineering problems, will remain just promises unless: all available knowledge forms are used; there is genuine interaction between research and industrial scientists and engineers to provide and make full use of this knowledge; and there is an understanding of the importance of knowledge based systems in science and engineering research and education.< >

关键词： Biomedical computing Knowledge representation neural networks Process control Real time systems

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Some developments towards analogue CMOS VLSI design

Some developments towards analogue CMOS VLSI design

引用

iee colloquium on VLSI Analogue Design

作者： D.G. Haigh J.T. Taylor K. Steptoe Department of Electronic and Electrical Engineering University College London UK

Recently, the possibility of 'real' analogue VLSI has begun to emerge. A system of this type may be loosely conceived of as a large chip, consisting primarily of high density analogue circuitry with a relatively smaller portion of digital circuitry for memory and control. In order to meet this challenge, it is clearly necessary to have at one's disposal, realisations for the basic system elements (or cells, e.g. operational amplifiers) which occupy small chip area, have low power consumption and still feature high precision performance. By adopting a firmly bottom-up approach, the authors examine different detailed aspects of analogue IC design which could help to bring the reality of analogue VLSI systems closer. These include continuous-time and discrete-time systems. They focus on minimisation of chip area and power consumption while maintaining high precision performance and consider complex analogue systems including artificial neural networks.< >

关键词： Design automation CMOS integrated circuits Integrated circuit fabrication Analog integrated circuits neural networks Switched capacitor circuits Very-large-scale integration

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