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International IEEE/EMBS Conference on neural Engineering, CNE

作者： D. Balya B. Roska Analogic and Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary Harvard Society of Fellows Harvard University Cambridge MA USA

The paper focuses on the input transformation for retinal implants. It describes a novel retina model, based on neurobiological measurements. Our modeling approach is neuromorphic, however the primary motivation is to derive an algorithmic skeleton from the animal retina measurements. The on-line, real-time implementation of the algorithm is given for an off-the-shelf stand-alone system, called Bi-I

关键词： Neuromorphics Retina Cochlear implants Optical transmitters Neurons Ear Biomedical acoustics Image restoration Signal restoration Stimulated emission

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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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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 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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Collision prediction via the CNN Universal Machine

Collision prediction via the CNN Universal Machine

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

作者： V. Gal T. Roska Analogical & Neural Computing Systems Laboratory at the computer Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Hungary

We present an analogic CNN algorithm that estimates the time to an impending collision between an approaching object and the observer. Calculation is based on a context insensitive method, which is well known in neuro... 详细信息

关键词： Cellular neural networks Turing machines Animals Equations Geometrical optics Object detection Image edge detection Detectors Pixel Optical arrays

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High speed stand-alone visual decision maker device based on focal plane analogic processor array chip

High speed stand-alone visual decision maker device based on...

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IEEE International Workshop on Virtual and Intelligent Measurement systems

作者： L. Torok A. Zarandy T. Roska Analogical & Neural Computing Systems Laboratory at Computer and Automation Research Institute of the Hungarian Academy of Sciences Budapest Hungary

ISBN: (纸本)0780365682

Newly emerging problems require high speed decision making based on visual perception of the environment. A project was set up to construct an intelligent agent like self-contained device that is capable to act in real-time and show collaborative behavior. Giving the hardware basis for decisions to be made a cellular nonlinear network CNN (Chua and Yang, 1988) chip implementation's optical input is used in combination with the cooperative devices' information that is received via binary ports and serial ports. The proposed design is a self-contained compact device that is prepared to operate stand-alone for up to 10 hours running on medium sized batteries while doing measurements, logging and collaborating with its environment via parallel port (for image transfer), RS-232 port (using modbus, profibus, PPP protocols) and binary I/O-s. Intelligent power module, optical isolation, watch dog capability is also considered.

关键词： Collaboration High speed optical techniques Nonlinear optics Decision making Visual perception Intelligent agent Hardware Cellular networks Cellular neural networks Nonlinear optical devices

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Optimal CNN templates for deconvolution

Optimal CNN templates for deconvolution

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

作者： L. Orzo Analogical & Neural Computing Systems Laboratory at the Computer and Automation Research Institute of the Hungarian Academy of Sciences Budapest Hungary

A simplified version of the gradient descent method is introduced as a straightforward way to find optimal 3/spl times/3 CNN templates for the inversion of known point spread functions (PSF). In practical applications the determination of this inverse is necessary to fulfil deconvolution tasks. The proposed method is much faster than the previously applied algorithms (like genetic algorithm) and still, in almost all practically important cases, it is convergent. Moreover, unlike a closed form method, it leads to 3/spl times/3 templates instead of 5/spl times/5 or bigger ones. In several important practical cases the PSF, which can be caused by motion, out of focus or the aberration of the imaging system, can be computed from object positions and from the optical system's parameters. Iterative deconvolution algorithms, which are necessary for volume reconstruction from microscopic image sequences, require considerable computation time. Using CNN-UM chips for these deconvolution tasks, a much higher speed, even real time processing seems to be achievable.

关键词： Cellular neural networks Deconvolution Genetic algorithms Focusing Optical imaging Optical computing Iterative algorithms Image reconstruction Microscopy Image sequences

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The CNN Universal Machine part 2: Programmability and applications 2

The CNN Universal Machine part 2: Programmability and applic...

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

作者： Roska, Tamás Chua, Leon O. Electronics Research Laboratory Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States Dual and Neural Computing Systems Laboratory Computer and Automation Institute of the Hungarian Academy of Sciences Kende-u.13/17 BudapestH-1111 Hungary

ISBN: (纸本)0780308751

The programmability (as a stored program) of the CNN Universal Machine is discussed first. It is shown why and in which sense this machine is universal. A new type of algorithm, the analogic one, is introduced. The application potential is reviewed and the biological relevance is analyzed. It turns out that the architecture is optimal not only for silicon implementations, however, many biological information processing organs have the same structure. © 1992 IEEE.

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