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5th IEEE International Conference on Electronics, Circuits and systems, ICECS 1998

作者： Zarándy, Ákos Keresztes, Péter Roska, Tamás Szolgay, Péter Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences P.O.B.63 BudapestH-1502 Hungary István Széchenyi Polytechnic Hédervári u. 3 GyôrH-9026 Hungary

ISBN: (纸本)0780350081

A new emulated digital CNN Universal Machine chip architecture is introduced in this paper. The chip contains 24 CNN core processors using 70mm2 silicon area with a 0.35 μm technology. Its speed is Ins/virtual cells/CNN iterations with 12 bits precision. This enables to execute over five hundred 3×3 convolutions on each frame of a 240×320 sized 25fps (standard NTSC) digital image flow. Another new feature of the design is the different precision capability. This allows the user to convert precision to speed. © 1998 IEEE.

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Optical tracking system for automatic guided vehicles using cellular neural networks

Optical tracking system for automatic guided vehicles using ...

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

作者： G. Eross T. Boros A. Kiss A. Radvanyi T. Roska J. Bito J. Vass Centre of Robotics and Automation Tungsram TH Company Limited Budapest Hungary Dual and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Budapest Hungary Department of information Technology Faculty of Engineering University of Veszprém Veszprem Hungary

A method for the path-control of automated guided vehicles (AGVs) in computer integrated manufacturing (CIM) systems that combines the flexibility and easy installation of optical methods with the simplicity and robustness of the inductive method is proposed. Using a new computing paradigm, the cellular neural network (CNN), and a related device, the VLSI CNN chip, a very high speed solution that is less expensive than the conventional methods can be achieved. This AGV control complies with the requirements of CIM systems. Further advantages of the proposed system are as follows: fault tolerance and the ability to give instructions along the path, and the use of a simple local control.< >

关键词： Vehicles computer integrated manufacturing Cellular neural networks High speed optical techniques Control systems Integrated optics Optical computing Robustness computer networks Very large scale integration

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Analogic Implementation of the Genetic Algorithm

Analogic Implementation of the Genetic Algorithm

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

作者： David Balya Viktor Gal Analogic and Neural Computing Systems Lab Computer and Automation Research Institute Budapest Hungary Function of Neural Circuits Laboratory Friedrich Miescher Institute for Biomedical Research Basel Switzerland

The CNN literature contains several papers about how to use the genetic algorithms for template tuning. This paper shows a possible CNN-UM implementation of the control algorithm of the genetic algorithm in a special fine-grained parallel version. The interesting of the analogic mapping is the different set of operators, which can be evaluated fast and efficient on the CNN-UM platform. The rational behind the spatial implementation is the possibility of focal-plane optimization

关键词： Genetic algorithms Biological cells Cellular neural networks Biomedical computing computer networks Evolution (biology) Algorithm design and analysis Genetic mutations Application software Application specific integrated circuits

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An accelerated digital CNN-UM (CASTLE) architecture by using the pipe-line technique

An accelerated digital CNN-UM (CASTLE) architecture by using...

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

作者： T. Hidvegi P. Keresztes P. Solgay Analogic and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Analogic and Neural Computing Systems Laboratory Hungarian Academy of Sciences Budapest Hungary István Széchenyi University Gyôr Hungary

Different CNN-UM architecture implementations, analog and emulated digital, were developed. The emulated digital architecture (CASTLE) is accurate but slower than the analog CNN-UMs. It is generally disadvantageous especially if transient computing is critical. The operation speed of the emulated digital implementations, namely CASTLE, can be increased significantly using the pipeline technique. This solution is analyzed with respect to area, time, etc. These arithmetic cores were tested and simulated using a VIRTEX FPGA development system.

关键词： Acceleration computer architecture Cellular neural networks Arithmetic Registers automation Image processing System testing Computational modeling Field programmable gate arrays

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Multi-scale image analysis on the CNN Universal Machine

Multi-scale image analysis on the CNN Universal Machine

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

作者： T. Kozek K.R. Crounse T. Roska L.O. Chua Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Nonlinear Electronics Laboratory University of California Berkeley CA USA

Algorithms for generating multi-scale representations of gray-scale images are presented. A number of possible approaches are described to produce low-pass and band-pass decompositions using simple analogic algorithms. It is also shown how the wavelet transform can be approximated with a similar technique and be used to obtain multi-level descriptions of the input data. This paper presents some methods how the cellular neural network (CNN) Universal Machine can be used effectively for generating multi-scale representations of gray-scale imagery.

关键词： Image analysis Cellular neural networks Turing machines Convolution Laplace equations Image processing Kernel Data mining Laboratories Wavelet transforms

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An Emulated Digital CNN Implementation

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Journal of VLSI signal processing systems for signal, image and video technology 1999年第2期23卷 291-303页

作者： Keresztes, Péter Zarándy, Ákos Roska, Tamás Szolgay, Péter Bezák, Tamás Hidvégi, Timót Jónás, Péter Katona, Attila István Széchenyi Polytechnic Győr Hungary Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest Hungary University of Veszprém Veszprém Hungary

A new emulated digital CNN Universal Machine chip architecture is introduced and the main steps of the design process are shown in this paper. One core processor can be implemented on 2 × 2 mm2 silicon area with a 0.35 μm CMOS technology. Assuming an array of 24 processors on a chip, its speed is 1ns/virtual cell/CNN iteration with 12 bit precision. This enables the execution of over five hundred 3 × 3 convolution operations on each frame of a 240 × 320-pixel 25 fps digital image flow. Another new feature of the design is its variable precision capability. This allows the user to trade off precision for speed. The architecture supports some non-linear filter implementation as well.

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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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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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Multitarget Tracking Applications of the Bi-i Platform: Attention-selection, Tracking and Navigation

Multitarget Tracking Applications of the Bi-i Platform: Atte...

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

作者： Gergely Timar Csaba Rekeczky Analogic and Neural Computing Systems Laboratory of the Computer and Automation Institute of the Hungarian Academy of Sciences Budapest Hungary Information Technology Department Pazmany Peter Catholic University Budapest Hungary

A multitarget tracking framework implemented on the Bi-i platform is presented. The demonstration applications include a target tracking system with laser actuation, an attention-selection algorithm and a laser dot de... 详细信息

关键词： Navigation Target tracking Cellular neural networks Application software computer networks Laser theory Circuits and systems Circuit testing Laboratories 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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