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
Fuzzy cellular neural networks: applications
TL;DR: This paper presents some typical applications of FCNN, such as gray-scale mathematical morphology and fuzzy inference edge detection, and a generalization of CNN by using fuzzy operations in the synaptic law calculation.
Journal ArticleDOI
Analog VLSI signal processing: why, where, and how?
TL;DR: This paper describes a simple model that captures all the essential features of the transistor and supports the concept of pseudoconductance which facilitates the implementation of linear networks of transistors.
Journal ArticleDOI
Convergence analysis of cellular neural networks with unbounded delay
TL;DR: A more general model of CNNs with unbounded delay is proposed, which may have potential applications in processing such motion related phenomena as moving images, and global convergence properties of this model are studied.
Journal ArticleDOI
Multistability in Recurrent Neural Networks
TL;DR: In this paper, the authors investigated the existence of multiple stable stationary solutions for Hopfield-type neural networks with delay and without delay and established a scenario of dynamics through formulating parameter conditions based on a geometrical setting.
Journal ArticleDOI
Operational transconductance amplifier-based nonlinear function syntheses
Edgar Sanchez-Sinencio,Jaime Ramirez-Angulo,Bernabe Linares-Barranco,Ángel Rodríguez-Vázquez +3 more
TL;DR: It is shown that the operational transconductance amplifier, as the active element in basic building blocks, can be efficiently used for programmable nonlinear continuous-time function synthesis.
References
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Neurons with graded response have collective computational properties like those of two-state neurons.
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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.