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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： C. Rekeczky I. Ushida T. Roska Department of Electrical and Electronics Engineering Faculty of Engineering University of Tokushima Tokushima Japan Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Size modification of binary pictures can be mapped onto the CNN array using space variant linear templates. However, if all the parameters have to be set for each cell individually, then one of the CNN's main advantages will be lost in practice, the simple and quick parallel reprogrammability. In this paper, a general methodology is presented to derive the space variant templates of the complete weighting matrix from control pictures applying a simple nonlinear space invariant template. The straightforward design method presumes a modified CNN architecture (multiple input and specific nonlinear voltage-controlled current sources in every cell) and can be extended for a large class of sparse weighting matrices. Following this strategy the diminishment and enlargement process has been investigated using constant cell current and various bias maps in the transformations.

关键词： Cellular neural networks Optical sensors Process control Output feedback Control systems

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Diminishment and Enlargement sf Binary Bictures BTsing Slightlgr Space Variant Cellular neural Netwo

Diminishment and Enlargement sf Binary Bictures BTsing Sligh...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： C. Rekeczky A. Ushida T. Roska Department of Electrical and Electronks Engineering Faculty of Engineering University of Tokushima Tokushima Japan Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

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SUBPIXEL PATTERN-RECOGNITION BY IMAGE HISTOGRAMS

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PATTERN RECOGNITION 1994年第8期27卷 1079-1092页

作者： SZIRANYI, T Analogical and Neural Computing Systems Research Laboratory Computer and Automation Institute Hungarian Academy of Sciences (MTA SZTAKI) P.O. Box 63 H-1518 Budapest Hungary

Recognition of small patterns covering only a few pixels in an image cannot be done by conventional recognition methods. A theoretically new pattern recognition method has been developed for undersampled objects which are (much) smaller than the window-size of a picture element (pixel), i.e. these objects are of subpixel size. The proposed statistical technique compares the gray-level histogram of the patterns of a set of scanned objects to be examined with the (calculated) gray-level densities of different (in shape or size) possible objects, and the recognition is based on this comparison. This method does not need high-precision movement of scanning sensors or any additional hardware. Moreover, the examined patterns should be randomly distributed on the screen, or a random movement of camera is (or target or both are) needed. Effects of noise are analysed, and filtering processes are suggested in the histogram domain. Several examples of different object shapes (triangle, rectangle, square, circle, curving lines, etc.) are presented through simulations and experiments. A number of possible application areas are suggested, including astronomy, line-drawing analysis and industrial laser measurements.

关键词： SUBPIXEL-RECOGNITION HISTOGRAM NOISE FILTERING UNDERSAMPLING SUPERRESOLUTION IMAGE ANALYSIS PATTERN CLASSIFICATION CONVOLUTION STATISTICAL PATTERN RECOGNITION LIGHT-SENSOR ARRAYS DENSITY ESTIMATION

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Transient response computation of a mechanical vibrating system using cellular neural networks

Transient response computation of a mechanical vibrating sys...

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

作者： P. Szolgay G. Voros Analogical and Neural Computing Laboratory. Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Technical Mechanics Budapest Hungary

Cellular neural networks (CNNs) paradigm is applied in the paper to compute the transient response of mechanical vibrating systems. Based on previous theoretical results on this field we would like to show (i) how the CNN templates can be generated automatically by a subroutine from the COSMOS/M finite element analysis system; (ii) how we assign to each degree of freedom two coupled CNN layers and how the templates are derived. Some interesting examples are shown and analyzed.< >

关键词： Transient response computer networks Cellular neural networks Finite element methods Symmetric matrices Differential equations Partial differential equations Algorithms Elasticity Damping

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A fast, complex and efficient test implementation of the CNN Universal Machine

A fast, complex and efficient test implementation of the CNN...

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

作者： J.M. Cruz L.O. Chua T. Roska Electronics Research Laboratory and Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Electronics Research Laboratory University of California Berkeley CA USA

In this paper we report on a fast, complex and efficient implementation of the Cellular neural Network Universal Machine as an IC chip. The chip has continuous time analog dynamics, and has been designed to process 50... 详细信息

关键词： Testing Cellular neural networks Turing machines Voltage Laboratories USA Councils Analog memory Logic circuits Programmable logic arrays Capacitors

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Novel types of analogic CNN algorithms for recognizing bank-notes

Novel types of analogic CNN algorithms for recognizing bank-...

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

作者： A. Zarandy F. Werblin T. Roska L.O. Chua Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Molecular Cell Biology 145-LSA University of California Berkeley CA USA Department of Electronics Research Laboratory University of California Berkeley USA

Novel types of analogic algorithms, using spatio-temporal CNN (cellular nonlinear/neural networks) operations are introduced. These algorithms make complex decisions in images without reading out the CNN chip. This makes them extremely time, area, and power effective. Two crucial effects are emphasized: diffusion type templates are applied during a finite time interval and local logic operates within well defined parts (patches) in the image plane. Hence, a new type of pattern recognition algorithm is introduced. The technique is demonstrated on an example. In our example we are dealing with an actual problem: how to avoid the counterfeiting on color copiers.< >

关键词： Cellular neural networks Turing machines Logic testing Laboratories Flowcharts Biological cells Image processing Cellular networks neural networks Counterfeiting

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Random parameter variation in analog VLSI neural networks for linear image filtering

Random parameter variation in analog VLSI neural networks fo...

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International Joint Conference on neural Networks (IJCNN)

作者： B.E. Shi T. Roska L.O. Chua Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA Dual and Neural and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

This paper introduces an analytic method to determine the sensitivity to random parameter variations of analog VLSI neural network architectures for linear image filtering. The authors compare the robustness of several different circuit architectures for low pass filtering. This method can also determine which components within a particular architecture should specified the most precisely.< >

关键词： Intelligent networks Very large scale integration neural networks Nonlinear filters Circuits Filtering Robustness Low pass filters computer architecture Cellular neural networks

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Deblurring of images by cellular neural networks with applications to microscopy

Deblurring of images by cellular neural networks with applic...

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

作者： J.P. Miller T. Roska T. Sziranyi K.R. Crounse L.O. Chua L. Nemes Division Neurobiology Department of Molecular & Cell Biology University of California Berkeley CA USA Analogic and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Electronics Research Laboratory Department of Electrical Engineering and Computer Science University of California Berkeley CA USA

In this paper it is shown how the Cellular neural Network (CNN) can be used to perform image and volume deblurring, with particular emphases on applications to microscopy. We discuss the basic linear theory of the CNN including issues of stability and template size. It is observed that a CNN with a small template can be used to implement an Infinite Impulse Response filter. It is then shown how general deblurring problems can be addressed with a CNN when the blurring operator is known. The proposed application is to solve the basic 3-D confocal image reconstruction task about the form of the blurring operator, confocal behavior in microscope images can be obtained with only 3-5 acquired image planes. In addition, the stored program capability of the CNN Universal Machine would provide integration of several image processing and detection tasks in the same architecture.< >

关键词： Cellular neural networks Microscopy Application software Biology computing computer networks Laboratories Stability Optical devices Optical distortion Image resolution

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HIGH-SPEED CHARACTER-RECOGNITION USING A DUAL CELLULAR neural-NETWORK ARCHITECTURE (CNND)

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 1993年第3期40卷 223-231页

作者： SZIRANYI, T CSICSVARI, J Analogic and Neural Computing Systems Research Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

An effective new character recognition procedure implemented on a new type of hardware system is proposed. This procedure applied a new architecture, called CNND. This CNND contains one or more analog cellular neural Networks (CNN) and some digital logic, incorporating the advantages of the fast analog CNN signal processing and the fast and easy decision capability of digital logics. This paper shows that this CNND system can be used for recognition of multifont printed or handwritten characters. Implemented in hardware, the system could hit the 100 000 char/s recognition speed with a recognition rate of more than 95 %. We show that the CNN results of pictures (maximum 40 * 40 pixels) of printed characters can be coded into about n * 20 bits (n = 2 ... 6) , so the coded results can be used to address memories of about 1 MB. The codes of CNN results of possible character pictures are used to address the memories while the memory contents are filled by the character categories. Prior to the hardware implementation the decision memories are filled by the results of recognition simulation for the possible pictures of each character-class in a filling procedure. In the memory filling procedure the simulated recognition uses a new random-type nearest neighbor (NN) method, which is ideal for the recent proposal of hardware applications. Recognition of handwritten characters is demonstrated in the same system with good recognition accuracy.

关键词： Character recognition Cellular neural networks Image edge detection Handwriting recognition neural networks Detectors Logic Hardware Charge coupled devices Filling

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FORMING AN INFORMATION TECHNOLOGY DEPARTMENT IN TURBULENT TIMES

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IEEE COMMUNICATIONS MAGAZINE 1992年第11期30卷 52-56页

作者： ROSKA, T Dual and Neural Computing Systems Research Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Hungary

The goals, objectives, characteristics, prerequisites, and courses of an information technology curriculum developed at the University of Veszprem in Hungary are discussed. Basic, introductory, and core courses as well as special subjects are listed, and the program schedule of the five years is presented. The place and role of information engineering in a changing world is discussed, including some thoughts on the role of information technology in the general university curricula.< >

关键词： Information technology Laboratories Education Educational technology automation Europe Mechanical engineering Electrical engineering computing Informatics Solids

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