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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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Hopf bifurcation analysis of a BAM neural network with multiple time delays and diffusion
Xiaohong Tian,Rui Xu,Qintao Gan +2 more
TL;DR: A BAM neural network with multiple time delays and diffusion under homogeneous Neumann boundary conditions is investigated and the local stability of the trivial uniform steady state and the existence of Hopf bifurcation under two different cases are established.
Journal ArticleDOI
Delay-Dependent Asymptotic Stability of Neural Networks with Time-Varying Delays
TL;DR: This paper considers the problem of stability analysis for neural networks with time-varying delays with the assumption that bounded delays are assumed to be bounded but not necessarily differ from one another.
Journal ArticleDOI
Design of an optoelectronic cellular processing system with a reconfigurable holographic interconnect
TL;DR: The design of an optoelectronic parallel processing system in which a reconfigurable computer-generated hologram is used to perform a shift-invariant optical interconnection operation is presented.
Journal ArticleDOI
Exponential attractors for first-order lattice dynamical systems
TL;DR: In this paper, the existence of an exponential attractor for the solution semigroup of a first-order lattice dynamical system acting on a closed bounded positively invariant set was investigated.
Journal ArticleDOI
A new global stability result for delayed neural networks
Qiang Zhang,Xiaopeng Wei,Jin Xu +2 more
TL;DR: By constructing suitable Lyapunov functionals and combining with matrix inequality technique, a new sufficient condition for the global asymptotic stability of delayed neural networks was presented in this paper.
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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Self Organization And Associative Memory
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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.