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2nd International Workshop on Cellular neural Networks and their Applications, CNNA 1992

作者： Szolgay, P. Kispál, I. Kozek, T. Dual and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences P.O.B.63 BudapestH-1502 Hungary Department of Information Technology Faculty of Engineering University of Veszprém Egyetem u. 10 VeszprémH-8201 Hungary

ISBN: (纸本)0780308751

Cellular neural networks (CNNs) are considered here as cellular analog programmable multidimensional processing arrays with distributed logic and memory. The interconnecting weights between the neighbouring processing elements are defined by the template *** the paper a new systematic way is presented to find robust templates. Using the new learning algorithm some templates were found for a CNN based layout design rule checking algorithm. The algorithm has been tested in our experimental system with real life examples. A typical design rule checking of a 432×164 pixels area takes 8s computation time on our CNN hardware accelerator board. © 1992 IEEE.

关键词： Cellular neural networks

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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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Tillarom: An AJAX based folk song search and retrieval system with gesture interface based on kodály hand

Tillarom: An AJAX based folk song search and retrieval syste...

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1st ACM International Workshop on Human-Centered Multimedia, HCM 2006, co-located with the 2006 ACM International Multimedia Conference

作者： Licsár, Attila Szirányi, Tamás Kovács, László Pataki, Balázs University of Pannonia Department of Image Processing and Neurocomputing Egyetem u. 10 H-8200 Veszprém Hungary Department of Distributed Systems Computer and Automation Research Institute Hungarian Academy of Sciences Lágymányosi u. 11 H-1111 Budapest Hungary Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Lágymányosi u. 11 H-1111 Budapest Hungary

ISBN: (纸本)1595935002

A digital folk song search and retrieval system with a hand gesture based interface is presented. Tillarom is a comprehensive collection of original Hungarian folk songs recorded using different technologies such as phonographs and/or stereo DAT cassettes. This digital archive contains professional quality metadata records as well as MIDI recordings for presenting the different types of clustered folk songs. An AJAX based search and retrieval interface was developed that can be used together with optically recognized Kodály's hand signs to formulate queries through a web browser. The appearance based recognition of hand gestures utilizes contour analysis and SVM based classification. We evaluated the performance of the recognition of hand signs and investigated the main problems of their usage in our system. Copyright 2006 ACM.

关键词： Information systems

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CNN chip set architectures and the visual mouse

CNN chip set architectures and the visual mouse

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

作者： T. Roska Analogical and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Electronics Research Laboratory University of California Berkeley Berkeley CA USA

The cellular neural network (CNN) Universal Machine architecture when implemented in VLSI chips needs special interfaces to provide for efficient system performance both in time (speed) and space (image size). The CNN chip set architectures described solve this problem, including interfacing the possibly analog input sensors and digital output and control. Various forms of CNN Engines are presented embedding CNN chip sets. A new device, the Visual Mouse, a hand held visual supercomputer, is also presented which exploits the genuine features of CNN Engines.

关键词： Cellular neural networks Mice computer architecture Microprocessors Engines computer interfaces Spatiotemporal phenomena Buffer storage Laboratories Turing machines

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Fast and efficient multi-layer CNN-UM emulator using FPGA

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Periodica Polytechnica Electrical Engineering 2003年第1-2期47卷 57-70页

作者： Nagy, Zoltán Szolgay, Péter Department of Image Processing University of Veszprém Egyetem u. 10 H-8200 Veszprém Hungary Analogic/Neural Computing Laboratory Computer and Automation Institute HAS Kende u. 13-17 H-1111 Budapest Hungary

A new emulated digital multi-layer CNN-UM chip architecture called Falcon has been developed. Simulation running time can be hundred times shorter using the Falcon processor array compared to the software simulation. This huge computing power makes real time image processing possible. In this paper the main steps of the FPGA implementation and optimization are introduced. The Distributed Arithmetic technique is used to optimize the architecture on FPGAs. Using this technique, smaller and faster arithmetic units can be designed than using conventional approach where multiplier cores and adder trees are used to compute the state equation of the CNN array.

关键词： Program processors

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An 0.5-/spl mu/m CMOS analog random access memory chip for TeraOPS speed multimedia video processing

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IEEE Transactions on Multimedia 1999年第2期1卷 121-135页

作者： R. Carmona-Galan A. Rodriguez-Vazquez S. Espejo-Meana R. Dominguez-Castro T. Roska T. Kozek L.O. Chua Instituto de Microelectronica de Sevilla Consejo Superior de Investigaciones Cientificas-Universidad de Sevilla Seville Spain MTA-SZTAKI Analogic and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Electronics Research Laboratory University of California Berkeley CA USA

Data compressing, data coding, and communications in object-oriented multimedia applications like telepresence, computer-aided medical diagnosis, or telesurgery require an enormous computing power-in the order of trillions of operations per second (TeraOPS). Compared with conventional digital technology, cellular neural/nonlinear network (CNN)-based computing is capable of realizing these TeraOPS-range image processing tasks in a cost-effective implementation. To exploit the computing power of the CNN Universal Machine (CNN-UM), the CNN chipset architecture has been developed-a mixed-signal hardware platform for CNN-based image processing. One of the nonstandard components of the chipset is the cache memory of the analog array processor, the analog random access memory (ARAM). This paper reports on an ARAM chip that has been designed and fabricated in a 0.5-/spl mu/m CMOS technology. This chip consists of a fully addressable array of 32/spl times/256 analog memory registers and has a packing density of 637 analog-memory-cells/mm/sup 2/. Random and nondestructive access of the memory contents is available. Bottom-plate sampling techniques have been employed to eliminate harmonic distortion introduced by signal-dependent feedthrough. Signal coupling and interaction have been minimized by proper layout measures, including the use of protection rings and separate power supplies for the analog and the digital circuitry. This prototype features an equivalent resolution of up to 7 bits-measured by comparing the reconstructed waveform with the original input signal. Measured access times for writing/reading to/from the memory registers are of 200 ns. I/O rates via the l6-line-wide I/O bus exceed 10 Msamples/s. Storage time at room temperature is in the 80 to 100 ms range, without accuracy loss.

关键词： Random access memory CMOS technology Image coding Image processing Cellular neural networks Registers Multimedia communication Multimedia computing Application software computer applications

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CNN Wave computing: Theory, Architectures, Implementations and Applicaions

CNN Wave Computing: Theory, Architectures, Implementations a...

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

作者： Marco Gilli Csaba Rekeczky Bertram Shi Department of Electronics Politecnico di Turino Torino Italy Analogic and Neural Computing Systems Laboratory of the Computer and Automation Information Technology Department Institute of the Hungarian Academy of Sciences Budapest Hungary Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong China

A cellular neural/nonlinear network (CNN) is any spatial arrangement of mainly locally coupled cells, where each cell is a dynamical system which has an input, an output and a state that evolves according to some prescribed dynamical laws. Since the CNN was first introduced in 1988, research in this field has developed rapidly. The goal of this tutorial is to provide participants with a snapshot of the current state of the art and research trends. It covers the broad multi-disciplinary areas of CNN research, from theoretical aspects to applications. The presenters have experience ranging from theoretical analysis of CNN dynamics, VLSI implementation and system level applications

关键词： Cellular neural networks computer architecture computer networks Very large scale integration Analog computers computer interfaces computer vision Biological system modeling Nonlinear dynamical systems computer industry

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The CNN universal machine. II. Programmability and applications

The CNN universal machine. II. Programmability and applicati...

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

作者： T. Roska L.O. Chua The Electronics Research Laboratory and Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA USA Dual and Neural Computing Systems Laboratory in the Computer and Automation Institute of the Hungarian Academy of Sciences Budapest Hungary

For pt.I, see ibid., p.1-10 (1992). The programmability (as a stored program) of the CNN universal machine is discussed. It is shown why and in which sense this machine is universal. The analogic type of algorithm is introduced. The application potential is reviewed and the biological relevance is analyzed. It is shown that the architecture is optimal not only for silicon implementations, but also for many biological information processing organs that have the same structure.< >

关键词： Cellular neural networks Turing machines Application software Laboratories neural networks Cloning Storage automation Silicon Information processing Cellular networks

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The CNN universal machine. I. The architecture

The CNN universal machine. I. The architecture

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

作者： L.O. Chua T. Roska The Electronics Research Laboratory and Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA USA Dual and Neural Computing Systems Laboratory in the Computer and Automation Institute of the Hungarian Academy of Sciences Budapest Hungary

Various types of cellular neural networks (CNNs) are summarized, and a taxonomy of CNNs is given according to the different types of grids, processors, interactions, and modes of operation. The CNN universal machine is introduced. The architecture and the key features of the CNN universal machine are outlined. An exhaustive list of references is given.< >

关键词： Cellular neural networks Turing machines computer architecture Grid computing Laboratories Taxonomy Optical computing Chaos Programmable logic arrays automation

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On the detection of critical frequencies of a tool machine

On the detection of critical frequencies of a tool machine

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

作者： P. Szolgay T. Szabo Analogical and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Mechanics University of Miskolc Egyetemváros Miskolc Hungary

An approximate solution is given for determining the ranges of allowed frequency of a mechanical model of a tool machine. The proposed method is based on the simulation of a measurement process of a real structure. The large computing power of cellular neural networks is used here to compute the transient response of a mechanical vibrating system.

关键词： Frequency Cellular neural networks computer networks Eigenvalues and eigenfunctions Computational modeling Finite element methods Mechanical systems Differential equations Laboratories automation

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