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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Journal ArticleDOI
Basic dynamics from a pulse-coupled network of autonomous integrate-and-fire chaotic circuits
Hidehiro Nakano,Toshimichi Saito +1 more
TL;DR: Basic classification of the phenomena and their existence regions can be elucidated in the parameter space and it is elucidated that the PCN exhibits interesting grouping phenomena based on the chaos synchronization patterns.
Journal ArticleDOI
Bifurcations and oscillatory behavior in a class of competitive cellular neural networks
TL;DR: It is shown that the interconnection symmetry, though ensuring complete stability, is not in the general case sufficient to guarantee that complete stability is robust with respect to sufficiently small perturbations of the interconnections.
Proceedings ArticleDOI
Recurrent perceptron learning algorithm for completely stable cellular neural networks
Cuneyt Guzelis,S. Karamahmut +1 more
TL;DR: The proposed algorithm RPLA has been applied for training CNNs to perform several image processing tasks such as edge detection, hole filling and corner detection and the performance of the templates obtained has been tested on a set of images which are different from the input images used in the training phase.
Journal ArticleDOI
CNN dynamics represents a broader class than PDEs
TL;DR: This work proves that the spatio-temporal CNN dynamics is broader than that described by PDEs, and there exist CNN models that are not equivalent to any PDE models, either because they do not approximate any Pde models, or because they have a qualitatively different dynamic behavior.
Journal ArticleDOI
Two-Dimensional Oscillatory Neural Network Based on Room-Temperature Charge-Density-Wave Devices
TL;DR: In this article, an oscillatory neural network implemented with two-dimensional (2-D) tantalum disulfide devices operating in the change density wave regime at room temperature is proposed.
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.
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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.