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
Uniqueness and stability of traveling waves for cellular neural networks with multiple delays
Zhi-Xian Yu,Ming Mei,Ming Mei +2 more
TL;DR: In this paper, the authors investigated the properties of traveling waves to a class of lattice differential equations for cellular neural networks with multiple delays and proved the uniqueness and the stability of these traveling waves.
Journal ArticleDOI
Toward CNN chip-specific robustness
TL;DR: A solution proposal to automatically tune templates in order to make the chip react as an ideal CNN structure and it is expected that as this technique matures, it will give CNN-UM chips enough reliability to compete with digital systems in terms of robustness in addition to advantages of speed.
Journal ArticleDOI
An LMI Approach for Dynamics of Switched Cellular Neural Networks with Mixed Delays
TL;DR: In this article, the authors considered the dynamics of switched cellular neural networks (CNNs) with mixed delays and provided sufficient conditions on the issue of uniformly ultimate boundedness, the existence of an attractor, and the globally exponential stability for CNNs.
Proceedings ArticleDOI
Arithmetic operations within memristor-based analog memory
M. Laiho,E. Lehtonen +1 more
TL;DR: This paper describes how memristors could be used as an analog memory and computing elements and requires a memristor model with a nonlinear programming sensitivity (programming threshold) for proper programming selectivity.
Journal ArticleDOI
Programmable analogue vlsi cnn chip with local digital logic
TL;DR: A new integrated circuit cellular neural network implementation with digitally or continuously selectable template coefficients is presented, providing a simple dual (analogue and digital) computing structure.
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.