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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： D. Balya C. Rekeczky T. Roska Analogical & Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary

The visual system is probably the most important sensory modality for humans as well as for mammals. Its first and best-known part is the retina, which is not a mere photoreceptor or static camera but a sophisticated feature preprocessor with a continuous input and several parallel output channels. These channels build up a "visual language" and any realistic mammalian retina model should generate the elements of this visual language. The framework of mammalian retinal modeling via multi-layer CNN has been recently published. In the present paper we show the transformation of this model into a CNN-UM algorithm and the design steps of the implementation of this complex visual language. The analogic algorithm consists of a series of different complex-cell CNN dynamics. The algorithm is feasible on a recently fabricated complex cell CNN-UM chip. The decomposition method of the multilayer mammalian retina model will be discussed in detail.

关键词： Retina Cellular neural networks Turing machines Visual system Humans Photoreceptors Cameras Data preprocessing Algorithm design and analysis Heuristic algorithms

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Basic mammalian retinal effects on the prototype complex cell CNN universal machine

Basic mammalian retinal effects on the prototype complex cel...

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

作者： D. Balya Cs. Rekeczky T. Roska Analogical & Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary

ISBN: (纸本)981238121X

The unique possibility for reconstructing the first stage of the visual system on a programmable silicon chip is described. The developed mammalian retinal model can be implemented as an analogic algorithm running on a prototype complex cell cellular neural network processor. It enables the neuro-biological and vision research communities to study the wisdom of biological visual transformations design in real-time. The operating prototype complex-cell CNN-UM processor opens a new world for the engineering as well as the computational neuroscience communities. This paper demonstrates the first steps in this direction. Here we present the decomposition and scaling of one retinal channel as a hardware-level CNN-UM algorithm. The analogic algorithm consists of a series of different complex-cell CNN spatial-temporal dynamics, feasible on the recently fabricated prototype complex cell CNN-UM chip.

关键词： Retina Prototypes Cellular neural networks Turing machines Neurons Target tracking Transfer functions

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Supervised and unsupervised art-like classifications of binary vectors on the CNN universal machine

Supervised and unsupervised art-like classifications of bina...

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

作者： D. Balya T. Roska Analogical & Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary

Fast and robust classification of feature vectors is a crucial task in a number of real-time systems. A cellular neural/nonlinear network universal machine (CNN-UM) can be applied very efficiently as a feature detector and also for post-processing the results for object recognition. This paper shows how a robust classification scheme based on adaptive resonance theory (ART) can also be mapped to the CNN-UM. The designed analogic CNN algorithm is capable of classifying the extracted binary feature vectors keeping the advantages of the ART networks. An analogic algorithm is presented for unsupervised classification with tunable sensitivity and automatic new class creation. Another CNN-UM algorithm is suggested for supervised classification. In addition to the two algorithms, a new "repair" function is proposed to reduce the number of the created classes. The presented binary feature vector classification is feasible on the existing standard CNN-UM chips.

关键词： Cellular neural networks Turing machines Robustness Subspace constraints Real time systems Cellular networks computer vision Object detection Detectors Object recognition

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High performance processor array for image processing

High performance processor array for image processing

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Peter Foldesy Akos Zarandy Csaba Rekeczky Tamas Roska Computer and Automation Research Institute of the Hungarian Academy of Sciences Analogic and Neural Computing Laboratory Budapest Hungary Eutecus Inc. Berkeley California USA AnaLogic Computers Budapest Hungary

The ASIC implementation of a digital cellular visual microprocessor architecture is introduced. The processor array is constructed of simple, locally interconnected 8 bit microprocessors, operating in an extended SIMD... 详细信息

关键词： Image processing Sensor arrays Xenon Pixel Silicon Arithmetic High performance computing Analog computers Filters Morphology

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Implementing a retinal visual language in CNN: A neuromorphic study

Implementing a retinal visual language in CNN: A neuromorphi...

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2001 IEEE International Symposium on Circuits and Systems, ISCAS 2001

作者： Werblin, F. Roska, B. Balya, D. Rekeczky, C. Roska, T. Vision Research Laboratory Department of Molecular and Cell Biology University of California at Berkeley Berkeley CA-94720 United States Analogical and Neural Computing Laboratory Computer and Automation Research Institute Lagymanyosi U. 11 Budapest H-1111 Hungary

ISBN: (纸本)0780366859

The retina sends to the brain a parallel set of about a dozen different space-time representations of the visual world. Each of these representations is generated by a distinct set of "feature detecting" transformations. These features most likely contain all the information we need and use to analyze and interpret the visual world. They constitute a fundamental visual language that is elaborated upon at higher centers in the brain. A multi-layer CNN is presented for mimicking this new retinal model. The model is composed of several prototype 3-layer CNN units, called Complex R-units. Surfaces of activity are represented by CNN layers. Various parameter sets represent the different parts of the multi-layer retinal model. The whole model can be described by a visual language with elementary instructions of a CNN Universal Machine containing the programmable Complex R-units. Decomposition methods in time and space are discussed. © 2001 IEEE.

关键词： Visual languages

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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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CNN Algorithms for Video Authentication and Copyright Protection

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Journal of VLSI signal processing systems for signal, image and video technology 1999年第2期23卷 449-463页

作者： Csapodi, Márton Vandewalle, Joos Preneel, Bart Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest Hungary ESAT SISTA/COSIC Laboratory Department of Electrical Engineering Katholieke Universiteit Leuven Leuven Belgium

This paper is concerned with the implementation of an image comparison algorithm and cryptographic hash functions on the regular array of cellular neural network (CNN) cells. These operations are necessary for message authentication and copyright protection in the multimedia service environment, serving both the interest of the copyright owner and the user. The basic problems of multimedia protection along with the requirements and role of the different actors in a multimedia service environment are also described here.

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Castle: An emulated digital CNN architecture;design issues, new results 5

Castle: An emulated digital CNN architecture;design issues, ...

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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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Some methods for practical halftoning on the CNN universal machine

Some methods for practical halftoning on the CNN universal m...

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

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

This paper explores two issues which are relevant in practical halftoning situations on the CNN universal machine: block processing of large images with small CNN arrays, and the use of no larger than 3/spl times/3 templates. It is shown that block processing can be performed without noticeable boundary artifacts by careful selection of boundary cell values. In this example, a standard 3/spl times/3 halftoning template is used; higher quality halftones can be obtained only by using larger templates. A CNNUM algorithm is introduced which uses only a 3/spl times/3 template but emulates a much larger effective template through an iterative procedure. The method is to discretize the CNN transient in time and then implement the spatial correlations at each time step with a CNN transient. An A-B-template pair was designed for a single CNN transient to approximate a very simple linear filter model of the human visual system. The resulting discrete-time system was analyzed. The iterative procedure is demonstrated to produce a visually pleasing halftone.

关键词： Cellular neural networks Turing machines Laboratories Iterative algorithms Humans Visual system Image processing Gray-scale automation Nonlinear filters

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Seismic wave propagation modelling on emulated digital CNN-UM architecture

Seismic wave propagation modelling on emulated digital CNN-U...

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

The synthetic seismogram has seen many years of widespread and successful application in geophysical prospecting. It is used to simulate the normal incidence reflectivity of a horizontally stratified medium and has been employed more recently to obtain the responses of subsurface structural and stratigraphie configurations. The solution of the partial differential equations of motion describing the propagation of stress waves in an elastic medium requires enormous computation power. In this paper a solution of seismic wave propagation will be presented on CNN-UM architecture. Unfortunately the space-dependent equations and the low computational precision do not make it possible to utilize the huge computing power of the analog CNN-UM chips so the Falcon emulated digital CNN-UM architecture is used to improve the performance of our solution.

关键词： Electromagnetic wave propagation

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