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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Book ChapterDOI
Soft Computing and its Applications
TL;DR: An overview of the essentials and applications of the soft computing paradigm is presented in this chapter with reference to the functionalities and operations of its constituent components.
Journal ArticleDOI
Detecting moving and standing objects using cellular neural networks
TL;DR: The general framework of motion detection based on discrete time samples of the moving image is defined and various cloning template sequences are proposed for detecting different types of motion.
Journal ArticleDOI
A 200 $\mu$ s Processing Time Smart Image Sensor for an Eye Tracker Using Pixel-Level Analog Image Processing
Dong Soo Kim,Gunhee Han +1 more
TL;DR: A smart sensor for an eye tracker using pixel-level analog image processing to eliminate the needs of many peripherals and the high power consumption of the conventional eye trackers is presented.
Journal ArticleDOI
New global exponential stability criteria for interval-delayed neural networks
TL;DR: In this paper, a Lyapunov-Krasovslii function combined with delay fractioning was proposed to guarantee the considered interval delayed cellular neural networks to be globally exponentially stable.
Journal ArticleDOI
Architecture of a Fully Pipelined Real-Time Cellular Neural Network Emulator
TL;DR: The proposed architecture has a fully pipelined structure, capable of processing full-HD 1080p@60 video streams, which is implemented on both high-end and low-cost FPGA devices, Altera Stratix IV GX 230, and Cyclone III C 25, respectively.
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.