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JournalISSN: 0098-4094

IEEE Transactions on Circuits and Systems 

Institute of Electrical and Electronics Engineers
About: IEEE Transactions on Circuits and Systems is an academic journal. The journal publishes majorly in the area(s): Digital filter & Network synthesis filters. It has an ISSN identifier of 0098-4094. Over the lifetime, 4327 publications have been published receiving 148882 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: 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. >

4,583 citations

Journal ArticleDOI
TL;DR: Examples of cellular neural networks which can be designed to recognize the key features of Chinese characters are presented and their applications to such areas as image processing and pattern recognition are demonstrated.
Abstract: The theory of a novel class of information-processing systems, called cellular neural networks, which are capable of high-speed parallel signal processing, was presented in a previous paper (see ibid., vol.35, no.10, p.1257-72, 1988). A dynamic route approach for analyzing the local dynamics of this class of neural circuits is used to steer the system trajectories into various stable equilibrium configurations which map onto binary patterns to be recognized. Some applications of cellular neural networks to such areas as image processing and pattern recognition 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. >

2,332 citations

Journal ArticleDOI
TL;DR: In this article, the analog-to-digital (A/D) conversion was considered as a simple optimization problem, and an A/D converter of novel architecture was designed.
Abstract: We describe how several optimization problems can be rapidly solved by highly interconnected networks of simple analog processors. Analog-to-digital (A/D) conversion was considered as a simple optimization problem, and an A/D converter of novel architecture was designed. A/D conversion is a simple example of a more general class of signal-decision problems which we show could also be solved by appropriately constructed networks. Circuits to solve these problems were designed using general principles which result from an understanding of the basic collective computational properties of a specific class of analog-processor networks. We also show that a network which solves linear programming problems can be understood from the same concepts.

2,149 citations

Journal ArticleDOI
TL;DR: In this article, a review of the algebras related to Kronecker products is presented, which have several applications in system theory including the analysis of stochastic steady state.
Abstract: The paper begins with a review of the algebras related to Kronecker products. These algebras have several applications in system theory including the analysis of stochastic steady state. The calculus of matrix valued functions of matrices is reviewed in the second part of the paper. This calculus is then used to develop an interesting new method for the identifiication of parameters of lnear time-invariant system models.

1,944 citations

Journal ArticleDOI
TL;DR: In this article, a modified nodal analysis (MNA) method is proposed, which retains the simplicity and other advantages of nodal Analysis while removing its limitations, and a simple and effective pivoting scheme is also given.
Abstract: The nodal method has been widely used for formulating circuit equations in computer-aided network analysis and design programs. However, several limitations exist in this method including the inability to process voltage sources and current-dependent circuit elements in a simple and efficient manner. A modified nodal analysis (MNA) method is proposed here which retains the simplicity and other advantages of nodal analysis while removing its limitations. A simple and effective pivoting scheme is also given. Numerical examples are used to compare the MNA method with the tableau method. Favorable results are observed for the MNA method in terms of the dimension, number of nonzeros, and fill-ins for comparable circuit matrices.

1,337 citations

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Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
20212
2020200
20192
20171
2016168
2015236