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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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Image compression by orthogonal decomposition and dynamic segmentation using cellular nonlinear network chips

Image compression by orthogonal decomposition and dynamic se...

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

作者： T. Sziranyi L. Czuni I. Kopilovic T. Gyimesi Analogical and Neural Computing Laboratory Hungarian Academy of Sciences Computer and Automation Institute Budapest Hungary Department of Image Processing 8z Neurocomputing University of Veszprém Veszprem Hungary

A method is shown using the CNN chip-set hardware architecture for the implementation of a high-speed, low bit-rate image coding system. A simple and fast algorithm is introduced to generate basis functions of 2 dimensional (2D) orthogonal transformations. Using the 2D basis functions of the Hadamard or Cosine functions, the transformation coefficients of the basic block of the image are measured by the CNN. Meanwhile, the CNN can produce the inverse transformation of the measured coefficients and the actual distortion-rate can be computed. If a required distortion-rate is reached, the coding process could be stopped (the use of even more coefficients would increase bit-rate needlessly). Effects of noise and VLSI computing accuracy are also considered to optimise the architecture. We also give a short description of how to join the transform coding method and the object-oriented image model.

关键词： Image coding Image segmentation Discrete cosine transforms Cellular neural networks Object oriented modeling Optimization methods computer networks Distortion measurement Nonlinear distortion Very large scale integration

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Diminishment and enlargement of binary pictures using slightly space variant cellular neural network architecture

Diminishment and enlargement of binary pictures using slight...

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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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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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Image inpainting methods by using CELLULAR neural networks

Image inpainting methods by using CELLULAR neural networks

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9th IEEE International Workshop on Cellular neural Networks and their Applications, CNNA

作者： Gacsádi, Alexandra Szolgay, Péter Electronics Department University of Oradea Str. Armatei Române Nr.5 410087 Oradea Romania Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences P.O.B.63 H-1502 Budapest Hungary Image Processing and Neurocomputing Department Veszprém University Egyetem u. 10 Veszprém Hungary

Some CNN methods are presented that can be used for the reconstruction of damaged or partially known images. The proposed methods take the possibility of direct implementation on an existing CNN chip into account, in a single step, by using 3*3 dimensional linear reaction templates. Due to complete parallel processing, computational time reduction is achieved. Efficiency of these methods can be increased by combining them with nonlinear template that ensures the growth of the local properties spreading area along with regional ones.

关键词： Cellular neural networks

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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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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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A dual CNN model of cyclopean perception and its application potentials in artificial steropsis

A dual CNN model of cyclopean perception and its application...

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

作者： A.G. Radvanyi Dual and Neural Computing Systems Laboratory Computer & Automation Stitute (MTA SZTAKI) Research Divsion Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Random-dot stereograms coding 3-D information in their internal correlation are used for probing human stereopsis. Dual cellular neural net (CNN) algorithms that can reveal 3-D surfaces coded in stereograms are reported. The concept of the difference stereogram is introduced and used for coding smooth surfaces. Its importance is due to the fact that difference stereograms of real objects can be created in an optical environment using a projector and camera.< >

关键词： Cellular neural networks Humans Cameras Application software Laboratories automation Visual system Retina Testing Image segmentation

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An experimental system for optical detection of layout errors of printed circuit boards using learned CNN templates 2

An experimental system for optical detection of layout error...

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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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CNN model of the feature-linked synchronized activities in the visual thalamo-cortical system

CNN model of the feature-linked synchronized activities in t...

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

作者： L. Orzo Z. Vidnyanszky J. Hamori T. Roska Lab. of Neurobiol. Semmuelweis Univ. Med. Sch. Budapest Hungary Laboratory of Neurobiology Semmelweis University Medical School Budapest Hungary Analogical and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

In order to investigate whether thalamic synchronization may contribute to the binding of different cortical representations in visual information processing, we made a neuromorphic model of the thalamo-cortical loop, using the cellular neural network (CNN) model and simulator. It is demonstrated with the aid of this model that the cortico-thalamic feedback by synchronizing dLGN relay cell responses, provides a temporal code and this may induce correlated activities in the target cortical neuron population. Our results support the notion that using synchronization of temporally structured activities as general integration mechanism, the processing of visual information occurs simultaneously in the highly interconnected thalamo-cortical system.

关键词： Cellular neural networks Biological system modeling Neurons Information processing Relays Laboratories Neuromorphics Analytical models Anatomy computer networks

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