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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
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Stability analysis in Lagrange sense for a class of BAM neural networks of neutral type with multiple time-varying delays
Jigui Jian,Baoxian Wang +1 more
TL;DR: In this paper, Lagrange stability for a class of neutral type BAM neural networks with multiple time-varying and bounded or unbounded delays is studied and the estimations of the positive invariant set, globally attractive set and globally exponentially attractive set are given.
Journal ArticleDOI
Integration and Co-design of Memristive Devices and Algorithms for Artificial Intelligence.
Wei Wang,Wenhao Song,Peng Yao,Yang Li,Joseph E. Van Nostrand,Qinru Qiu,Daniele Ielmini,Jianhua Yang +7 more
TL;DR: Novel brain-inspired algorithms are being proposed to utilize such behaviors as unique features to further enhance the efficiency and intelligence of neuromorphic computing, which calls for collaborations among electrical engineers, computing scientists, and neuroscientists.
Journal ArticleDOI
Multilayer RTD-memristor-based cellular neural networks for color image processing
TL;DR: A novel compact multilayer CNN model based on nanometer scale resonant tunneling diodes (RTDs) and memristors is presented and offers advantages of powerful processing capability as well as high compactness, versatility, and possibility of very large scale integration (VLSI) circuit implementations.
Journal ArticleDOI
Molecular Processors: From Qubits to Fuzzy Logic
TL;DR: It is demonstrated how it is possible to process different types of logic through molecules, as long as decoherent effects are maintained far away from a pure quantum mechanical system, quantum logic can be processed.
Journal ArticleDOI
On Stability of Cellular Neural Networks
Pier Paolo-Civalleri,Marco Gilli +1 more
TL;DR: The main results about stability of cellular neural networks (CNNs) are reviewed and some of them are extended and reformulated, with the purpose of providing to the CNN designer simple criteria for checking the stability properties.
References
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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.