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
Stability and bifurcation analysis of reaction–diffusion neural networks with delays
TL;DR: Stability and Hopf bifurcation of reaction–diffusion neural networks with delays is considered, where the sum of the delays can be regarded as a bIfurcation parameter.
Journal ArticleDOI
Genetically trained cellular neural networks
TL;DR: The Genetic Algorithm is proposed as a general training method for Cellular Neural Networks for specific greyscale image processing tasks using supervised learning information in the fitness function.
Journal ArticleDOI
A synthesis procedure for associative memories based on space-varying cellular neural networks
TL;DR: A synthesis procedure for obtaining a space-varying CNN that can store given bipolar vectors with certain desirable properties and can be efficiently solved by recently developed interior point methods is proposed.
Journal ArticleDOI
On differential equations with delay in Banach spaces and attractors for retarded lattice dynamical systems
TL;DR: In this article, the existence of a global compact attractor for a lattice dynamical system with delay was proved, assuming that the nonlinear term is in some sense weakly continuous.
Journal ArticleDOI
New chaotic memristive cellular neural network and its application in secure communication system
Chunbo Xiu,Ruxia Zhou,Yuxia Liu +2 more
TL;DR: Simulation results show that the new terminal sliding mode control has good robustness to the external disturbances and uncertainties of internal parameters, and the new chaotic memristive CNN system can be used in the secure communication by the chaos synchronization based on slidingmode control.
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.