Titlebook: Cellular Neural Networks and Analog VLSI; Leon O. Chua,Glenn Gulak,Angel Rodríguez-Vázquez Book 1998 Springer Science+Business Media New Y

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Analog VLSI Design Constraints of Programmable Cellular Neural Networks,ssing tasks. The robust design of analog VLSI requires a good understanding of the capabilities as well as the limitations of analog signal processing. Implementation-oriented theoretical methods are described to compute the effect of all types circuit non-idealities with random or systematic causes

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Focal-Plane and Multiple Chip VLSI Approaches to CNNs,ks: a programmable low-power CNN with embedded photosensors, a compact fixed-template CNN based on unipolar current-mode signals, and basic CMOS circuits to implement an extended CNN model using spikes. The first two VLSI approaches are intended for focal-plane image processing applications. The thi

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Analog VLSI Circuits for Competitive Learning Networks,al circuits for competitive learning are currently important for their applications in computationally-efficient speech and image compression by vector quantization, as required for example in portable multi-media terminals. A summary of competitive learning models is presented to indicate the type

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Design of Neural Networks Based on Wave-Parallel Computing Technique,enting neural networks. The fundamental concepts are the frequency multiplexing of signals on a single line, and their wave-parallel processing without decomposition. This paper discusses the realization of a Hopfield-type massively-connected neural network, and shows that the WPC-based network exhi

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oving area. ..Cellular Neural Networks and Analog VLSI. serves as an excellentreference, providing insight into some of the most challengingresearch issues in the field.978-1-4419-5030-7978-1-4757-4730-0