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The CNN universal machine. II. Programmability and applications

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

引用

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

引用

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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analogic computing: system aspects of analogic CNN sensor computers

Analogic computing: system aspects of analogic CNN sensor co...

引用

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

作者： T. Roska Analogical and Neural Computing Laboratory of the Computer and Automation Research Institute of the Hungarian Academy of Science Budapest and the Department of Information Technology Pfizmhy P. Catholic University Budapest Hungary

A new principle of computing and computers is emerging: the analogic cellular computer. Its architecture, the Cellular neural Net (CNN) Universal Machine, is now implemented in several different physical forms and the first practical experiments exhibit very good frame rate and computing power. Several "Kilo real-time video" frame rate (more than 10000 frames per second) and TeraOPS computing power on a 1 cm/sup 2/ CMOS (0.5 micron) chip were measured. In this review article, the systems aspects and the new directions in this field are considered. A new world of software and a new notion of computing are taking ground. The possibility of software in optical computing becomes feasible. Likewise, programming on atomic and molecular scale implementations may be possible. Hence, photons and molecules may be used for signal representation in these analogic computers.

关键词： Cellular neural networks Sensor systems Optical computing computer architecture neural networks Turing machines Physics computing Power measurement Semiconductor device measurement Atomic measurements

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Supervised training based hand gesture recognition system

Supervised training based hand gesture recognition system

引用

International Conference on Pattern Recognition

作者： A. Licsar T. Sziranyi Department of Image Processing and Neurocomputing University of Veszprém Veszprem Hungary Analogical & Neural Computing Laboratory Computer & Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

We have developed a hand gesture recognition system, based on the shape analysis of static gestures, for human computer interaction purposes. Our appearance-based recognition uses modified Fourier descriptors for the classification of hand shapes. As always found in literature, such recognition systems consist of two phases: training and recognition. In our new practical approach, following the chosen appearance-based model, training and recognition is done in an interactive supervised way: the adaptation for untrained gestures is also solved by hand signals. Our experimental results with three different users are reported. Besides describing the recognition itself we demonstrate our interactive training method in a practical application.

关键词： Shape Character recognition Image processing Laboratories automation Human computer interaction Application software Control systems Virtual environment Cameras

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Dynamic training of hand gesture recognition system

Dynamic training of hand gesture recognition system

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International Conference on Pattern Recognition

We developed an augmented reality tool for vision-based hand gesture recognition in a camera-projector system. Our recognition method uses modified Fourier descriptors for the classification of static hand gestures. Hand segmentation is based on a background subtraction method, which is improved to handle background changes. Most of the recognition methods are trained and tested by the same service-person, and training phase occurs only preceding the interaction. However, there are numerous situations when several untrained users would like to use gestures for the interaction. In our new practical approach the correction of faulty detected gestures is done during the recognition itself. Our main result is the quick on-line adaptation to the gestures of a new user to achieve user-independent gesture recognition.

关键词： computer displays Cameras Fault detection Mice Hardware Phase detection System testing Feedback Auditory displays Image processing

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A fast, complex and efficient test implementation of the CNN Universal Machine

A fast, complex and efficient test implementation of the CNN...

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

作者： J.M. Cruz L.O. Chua T. Roska Electronics Research Laboratory and Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Electronics Research Laboratory University of California Berkeley CA USA

In this paper we report on a fast, complex and efficient implementation of the Cellular neural Network Universal Machine as an IC chip. The chip has continuous time analog dynamics, and has been designed to process 50... 详细信息

关键词： Testing Cellular neural networks Turing machines Voltage Laboratories USA Councils Analog memory Logic circuits Programmable logic arrays Capacitors

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A Real-time Mammalian Retina Model Implementation on FPGA

A Real-time Mammalian Retina Model Implementation on FPGA

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

作者： Zoltan Nagy Zsolt Voroshazi Peter Szolgay Department of Image Processing and Neurocomputing University of Pannonia Veszprem Hungary Analogic and Neural Computing Laboratory Computer and Automation Institute of HAS Kende u. 13-17 H-1111 Budapest Hungary. e-mail: szolgay@sztaki.hu

This paper presents an extended emulated digital retina model to compute two different retina channels in video real-time. The proposed emulated digital implementation of the two-channel retina model is discussed in three different points of view: processing speed, number of physical cells and accuracy. A real-time test environment with camera input and display output is going to be set up to analyze the retina model implementation on emulated digital CNN model by using a 6M gate equivalent FPGA (Field Programmable Gate Array).

关键词： Retina Field programmable gate arrays Cellular neural networks Partial differential equations Cameras Displays Very large scale integration Application software Image processing Laboratories

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Some novel capabilities of CNN: game of life and examples of multipath algorithms

Some novel capabilities of CNN: game of life and examples of...

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

作者： L.O. Chua T. Roska P.L. Venetianer A. Zarandy Department of Electrical Engineering and Computer Sciences and the Electronics Research Laboratory University of California Berkeley Berkeley CA USA Dual and Neural Computing Systems Laboratory Computer & Automation Institute (MTA SzTAKI) Research Division Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

The authors show that the game of life algorithm, which is equivalent to a Turing machine, can be realized by cellular neural networks (CNNs). They also present a multipath CNN algorithm that demonstrates the capabilities of analog/logic (analogic) software. Complex image processing tasks can be realized by programmable dual computing CNNs. A specific example of blob-counting in a gray-scale image is presented.< >

关键词： Cellular neural networks Turing machines Laboratories Logic Analog computers Biological system modeling automation Games Fading neural networks

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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 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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