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CNN-based difference-controlled adaptive non-linear image filters

International Journal of Circuit Theory and Applications 1999年第4期26卷

作者： Csaba Rekeczky Tamás Roska Akio Ushida Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest Hungary Department of Electrical and Electronic Engineering Faculty of Engineering University of Tokushima Tokushima Japan

In this paper, we develop a common cellular neural network framework for various adaptive non-linear filters based on robust statistic and geometry-driven diffusion paradigms. The base models of both approaches are defined as difference-controlled non-linear CNN templates, while the self-adjusting property is ensured by simple analogic (analog and logic) CNN algorithms. Two adaptive strategies are shown for the order statistic class. When applied to the images distorted by impulse noise both give more visually pleasing results with lower-frequency weighted mean square error than the median base model. Generalizing a variational approach we derive the constrained anisotropic diffusion, where the output of the geometry-driven diffusion model is forced to stay close to a pre-defined morphological constraint. We propose a coarse-grid CNN approach that is capable of calculating an acceptable noise-level estimate (proportional to the variance of the Gaussian noise) and controlling the fine-grid anisotropic diffusion models. A combined geometrical–statistical approach has also been developed for filtering both the impulse and additive Gaussian noise while preserving the image structure. We briefly discuss how these methods can be embedded into a more complex algorithm performing edge detection and image segmentation. The design strategies are analysed primarily from VLSI implementation point of view; therefore all non-linear cell interactions of the CNN architecture are reduced to two fundamental non-linearities, to a sigmoid type and a radial basis function. The proposed non-linear characteristics can be approximated with simple piecewise-linear functions of the voltage difference of neighbouring cells. The simplification makes it possible to convert all space-invariant non-linear templates of this study to a standard instruction set of the CNN Universal Machine, where each instruction is coded by at most a dozen analog numbers. Examples and simulation results are given t

关键词： non-linear cellular neural networks CNN Universal Machine adaptive non-linear filters robust statistic filters geometry-driven diffusion

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Invertible operations on a Cellular Neural Network Universal Machine

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International Journal of Circuit Theory and Applications 1999年第6期26卷

作者： Márton Csapodi Joos Vandewalle Tamás Roska Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences P.O. Box 63 H-1502 Budapest Hungary ESAT Laboratory Department of Electrical Engineering Katholieke Universiteit Leuven K. Mercierlaan 94 B-3001 Leuven Belgium

This paper is concerned with the invertibility of parallel operations definable on two-dimensional binary arrays by means of a local Boolean function. In this way, it contributes to the theory of cellular automata and may open new potentialities to cellular neural network applications. We provide a theoretically new approach to the invertibility of two-dimensional additive maps which can be used to obtain detailed information on the behaviour of these operations. Other ways to make invertible operations are also investigated, including local maps which are additive in only one of the terms, and second-order cellular automata. The discussed techniques yield a rich variety of invertible operations on infinite and/or finite two-dimensional binary arrays. When implemented on CNN Universal Chips, all of these operations, performed by TeraOPS speed, become subroutines of a 2D analogic algorithm. These operations can be used in 2D cryptography. © 1998 John Wiley & Sons, Ltd.

关键词： CNN universal machine two-dimensional CA additive maps complementary landscapes

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Modelling and Control of Water Supply Systems

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IFAC Proceedings Volumes 1998年第20期31卷 543-548页

作者： Nedjeljko Perić Ivan Petrović Ante Magzan University of Zagreb Croatia Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation Končar-Electrical Engineering Institute Zagreb Croatia

A dynamical mathematical model of a water supply plant based on lumped parameters is described. A concept of its control system is proposed that ensures output pressure stabilisation under conditions of variable water consumption and variable water recourses. The control system consists of inner control loops which control the flow of each pump station and of a superimposed control loop that controls the output pressure of the water supply plant. The pressure controller calculates the cumulative reference value of the water flow for all controlled pumps and from this value an algorithm for the flow distribution calculates the reference flow for each inner loop, taking into account the level of water accumulation in each water well. Control performances of output pressure obtained by a conventional PI controller and a fuzzy logic based controller are compared.

关键词： Large-scale systems Pressure control Flow control Pipelines Plants Mathematical models Fuzzy control

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Comparison of the self-tuning generalized predictive controller and pole placement controller

Comparison of the self-tuning generalized predictive control...

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Mediterranean Electrotechnical Conference (MELECON)

作者： I. Santro N. Peric I. Petrovic Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Zagreb Croatia

The basic principles of the self-tuning generalized predictive controller (GPC) and the self-tuning pole placement controller are presented. A laboratory shell-and-tube heat exchanger is used to test the properties of the presented controllers. The self-tuning GPC were compared with the self-tuning pole placement controller regarding their parameter adjustment complexity, reference and disturbance step responses and robustness to differences between the real process and its mathematical model.

关键词： State feedback Automatic control Predictive models Optimal control Costing Cost function Control engineering computing Laboratories Testing Robust control

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Rudder servo-system fault diagnosis using neural network fault modeling

Rudder servo-system fault diagnosis using neural network fau...

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OCEANS

作者： Z. Vukic D. Pavlekovic H. Ozbolt Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Zagreb Croatia

The model based fault detection and identification scheme for the rudder servo system as the actuator in the closed loop course keeping control system is presented. The nonlinear process model that enables description of a wide class of fault types is given and the fault function as the residual for detecting and identifying the fault is introduced. A fault detection scheme with variable thresholds is suggested and its performance has been tested via simulation in the presence of modeling uncertainty and noise. A fault identification scheme based on comparison between the fault function estimate and the output of a predefined analytical fault model is suggested.

关键词： Fault diagnosis Neural networks Fault detection Control systems Automatic control Actuators Control system synthesis Redundancy Control engineering computing Computer networks

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Improved Fuzzy Autopilot for Track-Keeping

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IFAC Proceedings Volumes 1998年第30期31卷 123-128页

作者： Zoran Vukić Edin Omerdić Ljubomir Kuljaca University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation Unska 3 HR-10000 Zagreb Croatia University of Tuzla Faculty of Electrical and Mechanical Engineering Department of Control Engineering in Automation Franjevačka 2 BH-75000 Tuzla Bosnia and Herzegovina

Improved 2-input fuzzy autopilot for ship course control and 3-input fuzzy autopilot for track-keeping are proposed. Nonlinear model of a ship and a steering subsystem is used. The 3-input fuzzy autopilot uses heading signal, yaw rate signal and lateral offset from the nominal track to produce a command rudder angle. Input variable fuzzyfication, fuzzy associative memory rules and output set defuzzyfication are described. Obtaining of FAM rules for 3-input fuzzy is described. Dynamical behavior of 2 and 3-input fuzzy autopilot is compared. The influence of wave disturbance, sea current and external disturbance from a passing ship on track-keeping performance was analyzed.

关键词： Disturbance rejection Fuzzy control Nonlinear control systems Ship control

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Adriatic Sea noise spectrum measurement and polynomial approximation

Adriatic Sea noise spectrum measurement and polynomial appro...

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OCEANS

作者： D. Matika H. Ozbolt Ministry of Defense of the Republic of Croatia Zagreb Croatia Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Zagreb Croatia

Based on the research at the location "Middle Adriatic", the analysis of the noise spectrum of the Adriatic Sea is presented. The applied measurement method and necessary instrumentation, followed by the basic scheme of the measurement channel, are given. A representative Adriatic Sea noise spectrum for the particular location is given, with the sea state as a parameter. A regression analysis is made that led to an appropriate approximation polynomial of the spectrum.

关键词： Sea measurements Noise measurement Polynomials Frequency Low-frequency noise Wind speed Control engineering computing Noise level Rain Ice

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High speed calculation of cryptographic hash functions by CNN chips

High speed calculation of cryptographic hash functions by CN...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： M. Csapodi J. Vandewalle T. Roska Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary ESAT Laboratory Department of Electrical Engineering Katholieke Universiteit Leuven Leuven Belgium

The paper is concerned with the implementation of cryptographic hash functions on the regular array of simple cellular neural network (CNN) cells with periodic boundary conditions. Cryptographic hash functions enable message origin authentication and validation of message content integrity. A class of cryptographic hash functions-termed Cartesian authentication codes-provide provable (unconditional) security for message authentication between two mutually trustful parties sharing a secret key. We succeeded in implementing existing constructions of Cartesian authentication codes on today's CNN Universal Machine (CNN-UM) chips. Here we prove that rather complex (binary) arithmetic can be performed on a simple CNN chip, by providing an algorithm to implement a specific Cartesian authentication code based on the computation of a polynomial expression over a finite field. The bitrate of the computation is in the 100 Mbit/sec range with existing chips.

关键词： Cryptography Cellular neural networks Message authentication Laboratories Galois fields automation Boundary conditions Turing machines Arithmetic Bit rate

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On the chip implementation of analogic algorithms for optical detection of some layout errors of printed circuit boards

On the chip implementation of analogic algorithms for optica...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： K. Tomordi P. Foldesy P. Szolgay Analogic and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Image Processing and Neurocomputing Department Faculty of Engineering University of Veszprém Veszprem Hungary

Printed circuit board layout inspection methods are mostly based on local geometric information, therefore they are well suited to the cellular neural networks (CNN) paradigm. The wire break, the wire and isolation width violation and an "H" type short circuits detector analogic algorithms were tested on a 20*22 CNN Universal Machine (CNNUM) chip working in the CNN Chip Prototyping System (CCPS) and on the CNN Engine Board (CNNEB), and the results were compared to the commercially available inspection systems.

关键词： Cellular neural networks Inspection Wire Circuit testing Geometrical optics Optical computing Printed circuits Detectors System testing Turing machines

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Advanced manipulation for deep underwater sampling: the AMADEUS research project

Advanced manipulation for deep underwater sampling: the AMAD...

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IEEE Conference on Control Technology and Applications (CCTA)

作者： D.M. Lane G. Bartolini G. Cannata G. Casalino J.B.C. Davies G. Veruggio M. Canals C. Smith Institute of Marine Biology of Creete (IMBC) Crete Greece Department of Mechanical and Chemical Engineering (MCE) Heriot-Watt University Edinburgh UK Department of Computer Communications and System Science (DIST) Università di Genova Genoa Italy Institute for Naval Automation (IAN) CNR Genoa Italy Department of Computing and Electrical Engineering (CEE) Heriot-Watt University Edinburgh UK Department of Geology Geophysics and Paleontology University Autònoma de Barcelona Barcelona Spain

This paper describes the design, development and future activities for the ongoing EU MAST II and III programmes AMADEUS I and II. The AMADEUS is a project focusing on improving the dexterity and sensory abilities of underwater systems for grasping and manipulation of delicate and other objects. Phase I of the project was completed in May 1996, and has developed a prototype dextrous three fingered underwater dextrous gripper. Phase II is now underway to deploy the hand from an underwater robot arm and carry out wet trials with end users. This paper summarizes the major achievements obtained within the programme.

关键词： Sampling methods Fingers Grippers Grasping Sliding mode control Force sensors Prototypes Supervisory control Vibration control Computer architecture

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