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检索条件"机构=AnaLogical and Neural Computing Systems Laboratory"

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An adaptive resonance theory-based neural network capable of learning via representational redescription

An adaptive resonance theory-based neural network capable of...

引用

International Joint Conference on neural Networks (IJCNN)

作者： G. Bartfai Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

This paper introduces a neural network architecture called R2MAP, which is based on the representational redescription hypothesis in cognitive science and adaptive resonance theory (ART) neural networks. The R2MAP network learns to classify arbitrary sequences of input patterns using a re-iterative process whereby knowledge that gets embedded in the network via ARTMAP-style error-driven learning is redescribed and becomes available to it for further learning. The knowledge redescription phase is triggered when the perceived level of difficulty of the given task exceeds a certain threshold, and is achieved through the dynamic creation of new features that better distinguish between output classes. This way the R2MAP network is capable of learning complex, relational input-output dependencies that cannot be represented efficiently using solely the features extracted through ordinary learning of statistical relationships. A simple proof-of-concept example is presented to illustrate the main ideas. Some related work is also discussed.

关键词： Resonance neural networks Biological neural networks Subspace constraints Cognitive science Artificial neural networks Humans Laboratories Automation Computer science

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Multi-target tracking with stored program adaptive CNN universal machines

Multi-target tracking with stored program adaptive CNN unive...

引用

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

作者： C. Rekeczky G. Timar G. Cserey Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

This paper shows that the performance of multi-target tracking (MTT) systems can be significantly increased with stored program adaptive cellular array sensors. The primary motivation of the present work is to define a topographic microprocessor architecture for MTT with embedded sensors capable of operating in a process real-time manner. In the ongoing experiments it is assumed that the input data flow is acquired by a single array sensor and the data is processed on an adaptive CNN-UM architecture consisting of both a cellular nonlinear network (CNN) and digital signal processing (DSP) microprocessors. The algorithms designed for this combined hardware platform use adaptive multi-channel CNN solutions for instantaneous position estimation and morphological characterization of all visible targets and the DSP environment for distance calculation, gating, data association, track maintenance and dynamic target motion prediction. A special feature of the architecture is that it allows interactive communication between the sensor and the digital environment. The configuration of functional modules for various real-time applications is discussed. Using real-life video-flows, successful tracking of several maneuvering targets is demonstrated within the proposed adaptive multi-channel framework.

关键词： Cellular neural networks Turing machines Sensor arrays Digital signal processing Adaptive arrays Microprocessors Sensor phenomena and characterization Target tracking Sensor systems Cellular networks

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An optical CNN implementation with stored programmability

An optical CNN implementation with stored programmability

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： S. Tokes L. Orzo C. Rekeczky T. Roska A. Zarandy Analogical & Neural Computing Systems Laboratory at the Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

The objective of this paper is to provide a framework for the implementation of programmable Opto-Electronic Analogic CNN (POAC) Computers embedding CNN Universal Chips. Specifically, a new method for optical CNN implementation is provided and some details are experimentally studied. The POAC architecture includes the integration of an optical processing system, such as a joint transform correlator, with the fast spatio-temporal processing capabilities of a CNN-UM chip. We have built and tested an optical sub-unit of this experimental optoelectronic architecture to examine their processing capabilities for complex target recognition tasks. Preliminary result of these measurements will also be presented. The main idea is to introduce stored programmability into optical computing.

关键词： Cellular neural networks Nonlinear optics Optical filters Optical network units Correlators Computer architecture Embedded computing Optical computing Image processing Target recognition

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computing on silicon with trigger waves: Experiments on CNN-UM chips

Computing on silicon with trigger waves: Experiments on CNN-...

引用

2001 IEEE International Symposium on Circuits and systems, ISCAS 2001

作者： Rekeczky, Csaba Szatmari, Istvan Foldesy, Peter Analogical and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences Kende U. 13-17 Budapest 1111 Hungary Jedlik Laboratories Department of Information Technology Peter Pazmany Catholic University Szentkirdyi U. 28 Budapest 1088 Hungary

ISBN: (纸本)0780366859

In this paper, experimental results on Cellular neural Network Universal Machine (CNN-UM) chips will be presented. These analogic spatio-temporal visual microprocessors make it possible that one can use nonlinear waves as the basic kernels of algorithms solving filtering-reconstruction and/or detection-classification problems. Showing output results from series of experiments it will be demonstrated how trigger waves, the simplest nonlinear waves, can constructively be used in a number of important application areas. © 2001 IEEE.

关键词： Silicon

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CNN chip set architectures and the visual mouse

CNN chip set architectures and the visual mouse

引用

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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Locating and reading color displays with the bionic eyeglass

Locating and reading color displays with the bionic eyeglass

引用

European Conference on Circuit Theory and Design, ECCTD

作者： Kristof Karacs Tamas Roska Faculty of Information Technology Pázmány Péter Catholic University Budapest Hungary Analogical and Neural Computing Systems Laboratory MTA-SZTAKI Budapest Hungary

Digital, high contrast displays are getting wide-spread in public transport, public areas and offices due to their ability to update their contents. Finding and reading them is of great importance when navigating, which is one of the most important functions in the formerly proposed Bionic Eyeglass, a mobile navigation guide for blind and visually impaired people. In this paper we present a novel algorithm for color cellular visual microprocessors to localize displays in image flows and an enhanced algorithm to recognize numbers on them. The cellular wave algorithms for sign localization combine color information with spatial-temporal logic. Imminent properties of color displays as well as device specific details were considered during algorithmic design.

关键词： Displays Colored noise Filters Navigation Vehicles Sensor phenomena and characterization Shape Noise figure Image color analysis Information technology

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On the detection of critical frequencies of a tool machine

On the detection of critical frequencies of a tool machine

引用

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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ACE: a digital floating point CNN emulator engine

ACE: a digital floating point CNN emulator engine

引用

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

作者： B. Feher P. Szolgay T. Roska A.G. Radvanyi T. Sziranyi M. Csapodi K. Laszlo L. Nemes I. Szatmari G. Toth P.L. Venetianer Measurement and Instrument Engineering Department Technical University of Budapest Budapest Hungary Analogical and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

The architecture of ACE, a multiprocessor analogic cellular neural network (CNN) emulator engine consisting of 2 to 16 TMS320C40 floating point DSPs is introduced. The engine containing up to 512 Mbyte RAM (enough to store a 512/spl times/512/spl times/512 sized CNN cube) which can be controlled through its SCSI port. It can either accelerate the multilayer CNN simulator CNNM or be accessed directly from the high level, C-based analogic CNN language ACL to achieve the simulation speed of /spl sim/2.8 /spl mu/sec/cell/iteration/DSP for 3/spl times/3 linear templates.

关键词： Cellular neural networks Engines Computer architecture Digital signal processing Very large scale integration Programmable logic arrays Computational modeling Logic arrays Signal processing algorithms Hardware

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CNNUM-Based Methods Using Deformable Contours on Smooth Boundaries

CNNUM-Based Methods Using Deformable Contours on Smooth Boun...

引用

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

作者： Tamas Szabo Peter Szolgay Department of Image Processing and Neurocomputing Faculty of Information Technology University of Pannonia Veszprem Hungary Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

In this paper two methods are presented. A CNNUM-based method is shown to quantify the displacement of the normal interhemisperic bilateral symmetry line. The method uses a deformable open contouring technique. Anothe... 详细信息

关键词： Active contours Computed tomography Magnetic resonance Anatomical structure Image segmentation Biomedical imaging Electronic mail Computer networks Pixel Image resolution

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computing on silicon with trigger waves: experiments on CNN-UM chips

Computing on silicon with trigger waves: experiments on CNN-...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： C. Rekeczky I. Szatmari P. Foldesy Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Jedlik Laboratories Department of Information Technology Péter Pazmány Catholic University Budapest Hungary

ISBN: (纸本)0780366859

关键词： Silicon Cellular neural networks Shape Active contours Laboratories Microprocessors Object detection Image reconstruction Echocardiography Automation

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