Cellular neural networks
Published 6 January 2003
Leon O. Chua, Lei Yang
Citations408
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TL;DR
Examples of cellular neural networks which can be designed to recognize the key features of Chinese characters are presented and some theorems concerning the dynamic range and the steady states of Cellular neural networks are proved.
Abstract
A novel class of information-processing systems called cellular neural networks is proposed. Like neural networks, they are large-scale nonlinear circuits which process signals in real time. Like cellular automata, they are made of a massive aggregate of regularly spaced circuit clones, called cells, which communicate with each other directly only through their nearest neighbors. Some applications in such areas as image processing are demonstrated, albeit with only a crude circuit. In particular, examples of cellular neural networks which can be designed to recognize the key features of Chinese characters are presented. Some theorems concerning the dynamic range and the steady states of cellular neural networks are proved. In view of the near-neighbor interactive property of cellular neural networks, they are much more amenable to VLSI implementation than general neural networks.>
Keywords
Computer Science
Proceedings of the National Academy of SciencesNeural networks and physical systems with emergent collective computational abilities.
19,349 Citations1982J. J. Hopfield
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.
Springer series in information sciencesSelf-Organization and Associative Memory
8,770 Citations1989Teuvo Kohonen
Biological Cybernetics“Neural” computation of decisions in optimization problems
6,040 Citations1985J. J. Hopfield, David W. Tank
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.
IEEE Transactions on Circuits and SystemsCellular neural networks: theory
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IEEE Transactions on Circuits and SystemsCellular neural networks: applications
2,383 Citations1988Leon O. Chua, L. Yang
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IEEE Transactions on Circuits and SystemsSimple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit
2,173 Citations1986David W. Tank, J. J. Hopfield
It is described how several optimization problems can be rapidly solved by highly interconnected networks of simple analog processors, and it is shown that a network which solves linear programming Problems can be understood from the same concepts.
ScienceComputing with Neural Circuits: A Model
2,130 Citations1986J. J. Hopfield, David W. Tank
A new conceptual framework and a minimization principle together provide an understanding of computation in model neural circuits that represent an approximation to biological neurons in which a simplified set of important computational properties is retained.
IEEE Transactions on Circuits and SystemsNeural networks for nonlinear programming
1,111 Citations1988Michael Peter Kennedy, Leon O. Chua
By considering the total cocontent function, the solution of the canonical non linear programming circuit is reconciled with the problem being modeled and it is shown how the circuit can be realized using a neural network, thereby extending the results of D.W. Tank and J.J. Hopefield to the general nonlinear programming problem.
Neural NetworksNeural network models for pattern recognition and associative memory
407 Citations1989Gail A. Carpenter
This review outlines some fundamental neural network modules for associative memory, pattern recognition, and category learning andAdaptive filter formalism provides a unified notation.
Physical review. A, General physicsAssociative recall of memory without errors
378 Citations1987Ido Kanter, Haim Sompolinsky
A neural network which is capable of recalling without errors any set of linearly independent patterns is studied, and the spurious states of the network are studied in detail in the case of random uncorrelated patterns.
Journal of the Franklin InstituteIntroduction to nonlinear network theory
284 Citations1970Franklin F. Kuo
Proceedings of the National Academy of SciencesAnalog "neuronal" networks in early vision.
281 Citations1986Christof Koch, José L. Marroquín +1 more
This work illustrates this approach by implementing a specific analog network, solving the problem of reconstructing a smooth surface from sparse data while preserving its discontinuities, and suggests a novel computational strategy for solving early vision problems in both biological and real-time artificial vision systems.
IEEE Transactions on Circuits and SystemsUnifying the Tank and Hopfield linear programming circuit and the canonical nonlinear programming circuit of Chua and Lin
109 Citations1987Michael Peter Kennedy, Leon O. Chua
The linear programming network of Tank and Hopfield is shown to obey the same unifying stationary cocontent theorem as the canonical nonlinear programming circuit of Chua and Lin.
Springer series in advanced microelectronicsCellular Neural Networks
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IEEE International Conference on Neural NetworksWhy VLSI implementations of associative VLCNs require connection multiplexing
65 Citations1988Bailey, Hammerstrom
The authors show that multiplexing of interconnections is necessary for networks exhibiting poor locality, and show that it is more feasible to build a VLCN system with sharing or multiplexers than to build one with dedicated wires for each connection.
Biological CyberneticsAssociative recognition and storage in a model network of physiological neurons
40 Citations1986Joachim M. Buhmann, Klaus Schulten
A neural network model in which the single neurons are chosen to closely resemble known physiological properties is considered, finding that the local dynamics of the cell potentials and the synaptic strengths result in global cooperative properties of the network and enable the network to process an incoming flux of information and to learn and store patterns associatively.
A network system for image segmentation
19 Citations1989Cortes, Hertz
A neural network for segmentation of a blurred and noise-corrupted image that is tested on simple geometrical figures distorted by Gaussian blur and noise, and its performance is compared with that of other algorithms.