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1st IEEE Regional Conference on Aerospace control systems, AEROCS 1993

作者： Wann, Chin-Der Thomopoulos, S.C.A. Department of Electrical and Computer Engineering Pennsylvania State University Decision and Control Systems Laboratory University ParkPA16802 United States

A benchmark study of two self-organizing artificial neural network models, ART2 and DIGNET, is conducted. The architecture differences and learning procedures between these two models are compared. The performance of ART2 and DIGNET on data clustering and signal detection problems with noise or interference is investigated by comparative simulations. It is shown that DIGNET generally has faster learning and better clustering performance on the statistical pattern recognition problems. DIGNET has a simpler architecture, and the system parameters can be analytically determined from the self-organizing process. The threshold value used in DIGNET can be specifically determined from a given lower bound on the desirable signal-to-noise ratio (SNR). The networks discussed in this paper are applied and benchmarked against clustering and signal detection problems. © 1993 IEEE.

关键词： Clustering algorithms

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Comparative study of self-organizing neural networks

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International Workshop on Artificial Neural Networks, IWANN 1993

作者： Wann, Chin-Der Thomopoulos, Stelios C. A. Decision and Control Systems Laboratory Department of Electrical and Computer Engineering The Pennsylvania State University University ParkPA16802 United States

ISBN: (纸本)9783540567981

A benchmark study of self-organizing neural network models is conducted. The comparison of advantages and disadvantages of unsupervised learning artificial neural networks are discussed. The unsupervised learning artificial neural networks discussed in this paper include adaptive resonance theory (ART2), DIGNET, self-organizing feature map, and learning vector quantization (LVQ). For the benchmark study of artificial neural network applications on data clustering and pattern recognition problems with additive gaussian noise, we compare the performance of the unsupervised learning systems, ART2 and DIGNET. Results of computer simulation show that both AR.T2 and DIGNET achieve good performance on pattern clustering, but DIGNET is faster in the learning process and has better results on the overall clustering performance. © Springer-Verlag Berlin Heidelberg 1993.

关键词： Unsupervised learning

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Improved performance adaptive control under standard Mrac assumptions 1

Improved performance adaptive control under standard Mrac as...

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1st IEEE Regional Conference on Aerospace control systems, AEROCS 1993

作者： Papadakis, I.N.M. Thomopoulos, S.C.A. Department of Electrical and Computer Engineering Pennsylvania State University Decision and Control Systems Laboratory University ParkPA16802 United States

In this paper, an adaptive controller with improved transient and steady-state performance using parameter mismatch compensation and high-order tuning is presented. As in previous designs, the use of a properly designed signal, compensating for the effects of parameter mismatch on the output error, leads to "arbitrary" performance improvement. However, unlike previous designs based on first-order (classical) tuners, high-order tuning is necessary in order to avoid the effect of terms due to initial conditions on the output error. This constitutes a strong motivation for the use of high-order tuners in adaptive control which so far, were considered as more complicated alternatives to the classical first-order tuners. The proposed controller also provides robustness enhancement in the presence of bounded disturbances and/or a class of unmodeled dynamics or in the event of an adaptation switch-off end, as in classical model reference adaptive control, guarantees the exponential convergence of all errors to zero in the presence of sufficiently exciting reference inputs. © 1993 IEEE.

关键词： Tuners

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Coordinate logic filters in image processing applications

Coordinate logic filters in image processing applications

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IEEE Winter Workshop on Nonlinear Digital Signal Processing

作者： B.G. Mertzios K. Tsirikolias Automatic Control Systems Laboratory Department of Electrical Engineering Democritus University of Thrace Greece

In this paper we present a number of coordinate logic filters (CL) for image processsing applications. The CL filters execute coordinate logic operations among the pixels of the image. They are very efficient in various image processing applications such as lowpass and highpass filtering, magnification, erosion, dillation, opening, closing, skeletonization, coding, compression as well as edge detection and feature extraction. They may be seen as multi-binary morphological kind of filters and they can be easily and fast implemented using logic circuits or by cellular automata.

关键词： Filters Image processing Shape Filtering Image coding Smoothing methods Image edge detection Logic circuits Boolean functions

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Design Recovery for Relay Ladder Logic

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IEEE control systems 1993年第2期13卷 90-98页

作者： Falcione, Albert Allen-Bradley Company Highland Heights OH 44143 747 Alpha Drive United States Laboratory for Automatic Systems and Information Processing Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA 15213 United States

An algorithm for converting relay ladder logic (RLL) programs for programmable logic controllers (PLCs) into sequential function chart (SFC) programs is introduced. Since an SFC (a standardization of Grafcet) better represents the sequential flow of control logic, it is considerably easier to understand and modify SFC programs. The practical motivation for this article is to provide a tool for converting existing RLL programs into SFC programs by recovering the underlying sequential control logic. This conversion of the program representation is referred to as design recovety. A basic design recovery algorithm is presented and applied to a simple RLL program for one stage of a batch chemical process. Several fundamental issues in discrete control logic representation and analysis are also identified as fertile areas for future research. © 1993 IEEE

关键词： Relays Logic design Programmable control Algorithm design and analysis automatic control Logic programming Chemical processes Industrial control computer languages Process control

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A METHOD FOR OPTIMAL STEP ADJUSTMENT FOR A CLASS OF LINEAR-QUADRATIC OPTIMAL-control PROBLEMS

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JOURNAL OF DYNAMIC systems MEASUREMENT AND control-TRANSACTIONS OF THE ASME 1993年第3期115卷 535-538页

作者： THOMOPOULOS, SCA PAPADAKIS, INM Decision and Control Systems Laboratory Department of Electrical and Computer Engineering The Pennsylvania State University University Park PA 16802

In this paper, a new method for the computation of the optimal step in gradient algorithms for a class of linear quadratic optimal control problems is presented. This method improves the convergence of the gradient al... 详细信息

关键词： Optimal control Gradient methods Computation

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computer-aids for modelling and conceptual design

Computer-aids for modelling and conceptual design

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IEEE International Conference on systems, Man and Cybernetics

作者： P.C. Breedveld Electrical Engineering Department Control Systems and Computer Engineering Group Control Laboratory and Mechatronics Research Centre Twente University of Twente Enschede Netherlands

The author identifies incentives for the use of computer-aids in modelling and design of physical systems and discusses possible solutions.

The author identifies incentives for the use of computer-aids in modelling and design of physical systems and discusses possible solutions.< >

关键词： systems engineering and theory Production control systems Mechatronics Physics computing Process design Digital simulation Cultural differences Mathematics control engineering computing

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Improved Performance MRAC of Linear and Nonlinear systems

Improved Performance MRAC of Linear and Nonlinear Systems

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American control Conference (ACC)

作者： Ioannis N. M. Papadakis Stelios C. A. Thomopoulos Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA

The problem of improved performance adaptive control (IPAC) of a class of linear and nonlinear systems is considered. A method for its solution is presented, the main feature of which lies in augmenting the "standard" model reference adaptive controller by a properly designed signal compensating for the effect of plant parameter uncertainty on the output error. One of the main performance improvement characteristics of the proposed IPAC is that the zero-state output error can be made arbitrarily small under standard model reference adaptive control (MRAC) assumptions in the case of linear systems while a similar result holds for a class of linearizable systems as well. The exponential convergence of the output and parameter errors in the presence of sufficiently rich reference inputs, remains a valid property of this controller which also achieves improved robustness in the presence of bounded disturbances and/or unmodeled dynamics as well as in the case of an adaptation switch-off.

关键词： Nonlinear systems Adaptive control Convergence Programmable control control systems Polynomials Linear systems Uncertain systems Frequency Performance gain

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Improved Performance Adaptive control Under Standard Mrac Assumptions

Improved Performance Adaptive Control Under Standard Mrac As...

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IEEE Regional Conference on Aerospace control systems

作者： I.N.M. Papadakis S.C.A. Thomopoulos Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA

关键词： Adaptive control Programmable control Tuners Signal design control systems Convergence Stability analysis Laboratories Displays Transient analysis

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Comparative Study of Self-Organizing Neural Networks in Signal Detection and Classification

Comparative Study of Self-Organizing Neural Networks in Sign...

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IEEE Regional Conference on Aerospace control systems

作者： Chin-Der Wann S.C.A. Thomopoulos Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA

关键词： Neural networks Intelligent networks Signal detection Artificial neural networks Pattern recognition Supervised learning Clustering algorithms Signal processing Resonance Partitioning algorithms

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