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
Traveling waves in cellular neural networks
TL;DR: In this paper, the authors studied the structure of traveling wave solutions of cellular neural networks of the advanced type and showed the existence of monotone traveling wave, oscillating wave and eventually periodic wave solutions by using shooting method and comparison principle.
Proceedings ArticleDOI
Single-layer CNN simulator
Chi-Chien Lee,J.P. de Gyvez +1 more
TL;DR: An efficient algorithm exploiting the latency properties of Cellular Neural Networks along with numerical integration techniques is reported; simulation results and comparisons are also presented.
Journal ArticleDOI
A Cellular Neural Network methodology for the automated segmentation of multiple sclerosis lesions.
Antonio Cerasa,Eleonora Bilotta,Antonio Augimeri,Andrea Cherubini,Pietro Pantano,Giancarlo Zito,Pierluigi Lanza,Paola Valentino,Maria Cecilia Gioia,Maria Cecilia Gioia,Aldo Quattrone +10 more
TL;DR: An automated approach capable of automatically determining the lesion load in multiple sclerosis patients from magnetic resonance imaging (MRI) gives satisfactory results showing that after the learning process the CNN is capable of detecting MS lesions with different shapes and intensities.
Journal ArticleDOI
Selectable and Unselectable Sets of Neurons in Recurrent Neural Networks With Saturated Piecewise Linear Transfer Function
Lei Zhang,Zhang Yi +1 more
TL;DR: The concepts of selectable and unselectable sets are proposed to describe some interesting dynamical properties of a class of recurrent neural networks (RNNs) with saturated piecewise linear transfer function and the problem of group selection is discussed by using such concepts.
Journal ArticleDOI
Tunneling-Based Cellular Nonlinear Network Architectures for Image Processing
TL;DR: A comparative study between different CNN implementations reveals that the RTD-based CNN can be designed superior to conventional CMOS technologies in terms of integration density, operating speed, and functionality.
References
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Neural networks and physical systems with emergent collective computational abilities
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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.