The paper presents a contribution to the analysis of wavelet transfer function use in neural network systems and the discussion of some possible learning algorithms of such structures. Wavelets local properties both i...
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The paper presents a contribution to the analysis of wavelet transfer function use in neural network systems and the discussion of some possible learning algorithms of such structures. Wavelets local properties both in time and frequency domains are stated at first giving motivation for wavelet networks application and providing bases for their initial coefficient estimation described recently. The main part of the paper is devoted to the network coefficients optimization using genetic algorithms as an alternative to the gradient descent method. Principles of the evolution techniques are presented for a simple system and then applied to a given time series modelling and prediction.< >
An experimental system was built up and tested for optical path tracking of a robot, where a 16*16 connected component detector chip with direct optical input was used. The speed of computation in the experimental arc...
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An experimental system was built up and tested for optical path tracking of a robot, where a 16*16 connected component detector chip with direct optical input was used. The speed of computation in the experimental architecture was analyzed.< >
A good model is essential in simulating and analyzing a system satisfactorily. This paper proposes a new computer-aided modelling methodology to construct parsimonious models for dynamic physical systems. A set of dom...
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A good model is essential in simulating and analyzing a system satisfactorily. This paper proposes a new computer-aided modelling methodology to construct parsimonious models for dynamic physical systems. A set of domain-independent modelling principles and domain-dependent modelling constraints has been formulated to guide parsimonious model construction. Models and the knowledge base for the enhancement of models have been described by bond graphs. After a parsimonious model is generated, two types of qualitative analysis are conducted;one is to derive unknown states from known states and the other is to predict the effects of parameter changes on the whole system. This methodology is only applicable when the structure of a dynamic system is known beforehand. A detailed case study is presented to demonstrate this approach.
The recent developments in Eastern Europe have allowed Western countries to influence the development of engineering in the Ukraine. This paper deals with the department of Information computing Systems and control in...
The recent developments in Eastern Europe have allowed Western countries to influence the development of engineering in the Ukraine. This paper deals with the department of Information computing Systems and control in the Institute of National Economy, Ternopol. Their course structure is discussed along with plans for the future.
A novel method for detecting incipient faults in controlled processes and assisting subsequent fault diagnosis is presented. Techniques that are applicable to a wide range of process units and robust to process distur...
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Applications of model-based fault detection methods in the chemical industry have been limited because of the difficulties posed in theoretically modelling these processes. This paper presents a novel fault detection ...
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Applications of model-based fault detection methods in the chemical industry have been limited because of the difficulties posed in theoretically modelling these processes. This paper presents a novel fault detection method based on estimating and monitoring a dynamic process model that is not obtained by theoretical modelling techniques. The method is aimed at detecting incipient faults in a wide range of controlled process units, and is demonstrated, in both simulations and practically on a laboratory test rig, by applications to incipient fault detection in a noisy, nonlinear process under digital computer control.
Two linear programming (LP) algorithms for the integrated state estimation (ISE) for the whole system are formulated and tested. It was found that a direct application of an ISE on a large power system suffers certain...
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Two linear programming (LP) algorithms for the integrated state estimation (ISE) for the whole system are formulated and tested. It was found that a direct application of an ISE on a large power system suffers certain limitations. This paper presents an efficient and reliable two-level state estimator (TLSE) based on LP techniques. Both the ISE and the proposed TLSE were tested under different conditions. The results are discussed and comparisons are given which show that the TLSE has many advantages over the ISE.
Many design problems, including control design problems, involve infinite dimensional constraints. Recent algorithms for solving design problems having such constraints are summarized.
Many design problems, including control design problems, involve infinite dimensional constraints. Recent algorithms for solving design problems having such constraints are summarized.
An approximate method of calculating the contributions of the gains in a feedback structure is produced. The discrete time, linear, quadratic state feedback problem is considered. By state and control augmentation dyn...
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An approximate method of calculating the contributions of the gains in a feedback structure is produced. The discrete time, linear, quadratic state feedback problem is considered. By state and control augmentation dynamic compensators with fixed and tunable parameters including decentralized and hierarchal structures can, also, be handled. An example is used to illustrate the usefulness of the approach in selecting good simplified feedback structures and to verify the reasonableness of the assumptions.
We present an algorithm for solving singular value inequalities over a continuum of frequencies. The algorithm is in two parts: a master algorithm which constructs an infinite sequence of finite sets of inequalities a...
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We present an algorithm for solving singular value inequalities over a continuum of frequencies. The algorithm is in two parts: a master algorithm which constructs an infinite sequence of finite sets of inequalities and a nondifferentiable optimization subalgorithm which solves these finite sets of inequalities.
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