Journal ArticleDOI
Cellular neural networks: theory
Leon O. Chua,L. Yang +1 more
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TLDR
In this article, a class of information processing systems called cellular neural networks (CNNs) are proposed, which consist of a massive aggregate of regularly spaced circuit clones, called cells, which communicate with each other directly through their nearest neighbors.Abstract:
A novel class of information-processing systems called cellular neural networks is proposed. Like neural networks, they are large-scale nonlinear analog circuits that process signals in real time. Like cellular automata, they consist of a massive aggregate of regularly spaced circuit clones, called cells, which communicate with each other directly only through their nearest neighbors. Each cell is made of a linear capacitor, a nonlinear voltage-controlled current source, and a few resistive linear circuit elements. Cellular neural networks share the best features of both worlds: their continuous-time feature allows real-time signal processing, and their local interconnection feature makes them particularly adapted for VLSI implementation. Cellular neural networks are uniquely suited for high-speed parallel signal processing. >read more
Citations
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Proceedings ArticleDOI
Low power VLSI neuron cells for artificial neural networks
Krzysztof Wawryn,B. Strzeszewski +1 more
TL;DR: Novel AB class neuron structures that set foundations for low power VLSI neural networks and other applications are proposed and a qualitative comparison is made between standard and proposed neuron cells.
Tactile sensing and analogic algorithms
TL;DR: A proactive-adaptive, multi-modal sensingprocessing-actuating investigation system based on behavior patterns observed in nature that provides essential information for dexterous telemanipulation.
Journal ArticleDOI
Non-linear coupled CNN models for multiscale image analysis
TL;DR: It is shown that in the isotropic case the two models are not topologically equivalent; in particular, discrete CNN models allow one to obtain the output image without stopping the image evolution after a given time (scale).
Journal ArticleDOI
The learning problem of multi-layer neural networks
Jung-Chao Ban,Chih-Hung Chang +1 more
TL;DR: This manuscript considers the learning problem of multi-layer neural networks (MNNs) with an activation function which comes from cellular neural networks, and the recursive formula of the transition matrix of an MNN is obtained.
Journal ArticleDOI
A recurrent dynamic neural network for noisy signal representation
TL;DR: A new recurrent dynamic neural network approach to solve noisy signal representation and processing problems by solving for the sets of representation coefficients required to model a given signal in terms of basis elementary signals.
References
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Journal ArticleDOI
Neural networks and physical systems with emergent collective computational abilities
TL;DR: A model of a system having a large number of simple equivalent components, based on aspects of neurobiology but readily adapted to integrated circuits, produces a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size.
Book
Self Organization And Associative Memory
TL;DR: The purpose and nature of Biological Memory, as well as some of the aspects of Memory Aspects, are explained.
Journal ArticleDOI
Neurons with graded response have collective computational properties like those of two-state neurons.
TL;DR: A model for a large network of "neurons" with a graded response (or sigmoid input-output relation) is studied and collective properties in very close correspondence with the earlier stochastic model based on McCulloch - Pitts neurons are studied.
Book
Neurons with graded response have collective computational properties like those of two-state neurons
TL;DR: In this article, a model for a large network of "neurons" with a graded response (or sigmoid input-output relation) is studied, which has collective properties in very close correspondence with the earlier stochastic model based on McCulloch--Pitts neurons.
Journal ArticleDOI
Neural computation of decisions in optimization problems
John J. Hopfield,David W. Tank +1 more
TL;DR: Results of computer simulations of a network designed to solve a difficult but well-defined optimization problem-the Traveling-Salesman Problem-are presented and used to illustrate the computational power of the networks.