Waleed Fakhr, Mohamed I. Elmasry (auth.), Mohamed I. Elmasry's VLSI Artificial Neural Networks Engineering PDF

By Waleed Fakhr, Mohamed I. Elmasry (auth.), Mohamed I. Elmasry (eds.)

ISBN-10: 146136194X

ISBN-13: 9781461361947

ISBN-10: 146152766X

ISBN-13: 9781461527664

Engineers have lengthy been enthusiastic about how effective and the way speedy organic neural networks are in a position to acting such advanced projects as popularity. Such networks are able to spotting enter information from any of the 5 senses with the mandatory accuracy and velocity to permit residing creatures to outlive. Machines which practice such complicated initiatives as attractiveness, with comparable ac­ curacy and pace, have been tricky to enforce till the technological advances of VLSI circuits and structures within the past due 1980's. given that then, the sector of VLSI synthetic Neural Networks (ANNs) have witnessed an exponential progress and a brand new engineering self-discipline was once born. this day, many engineering curriculums have incorporated a path or extra at the topic on the graduate or senior lower than­ graduate degrees. because the pioneering booklet by way of Carver Mead; "Analog VLSI and Neural Sys­ tems", Addison-Wesley, 1989; there have been a few very good textual content and ref­ erence books at the topic, every one facing one or issues. This booklet makes an attempt to give an built-in method of a unmarried examine group to VLSI ANNs Engineering.

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Such a vigilance test is incorporated into the adaptive backward network. Similarities between the ART framework and adaptive k-means algorithm have been recently discussed in [45]. 2 19 The Self-Organizing Feature Map Suppose that an input pattern has N features and is represented by a vector a: in an N-dimensional pattern space. The network maps the input patterns to an output space. The output space in this case is assumed to be one-dimensional or two-dimensional arrays of nodes, which possess a certain topological order.

1) R 411 = 1411 S (a) <>---:::J...... 2 (a) An NMOS transistor (b) Equivalent resistance (c) Controlling clock A Sampled-Data VLSI ANN Recognition System 45 where, lav is the average current passing through the MOS during the whole period of time T. T [VsR- lav = Ioff dt] VD . 2) T)] T+ VsR-offVD . (T _ T)] ~ [Vs;onVD ] . 6) Therefore, SR technique operates on a pulse width control principle in which the value of each element is determined by the duty-cycle of a single digitally controlled analog transmission gate.

1. Burke; "Clustering Characterization of Adaptive Resonance". 4, pp. 485-491, 1991. [46] K. Fukushima, S. Miyaki, and T. Ito; "Neocognitron: A Neural Network Model for a Mechanism for Visual Pattern Recognition". IEEE Transactions on Systems, Man and Cybernetics, SMC-13. pp. 826-834, 1983. [47] IJ. W. Tank; "Neural Computation of Decision in Optimization Problems". Biological Cybernetics, 52, pp. 141-152,1985. 2 A SAMPLED-DATA CMOS VLSI IMPLEMENTATION OF A MULTI-CHARACTER ANN RECOGNITION SYSTEM Sameh E.

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VLSI Artificial Neural Networks Engineering by Waleed Fakhr, Mohamed I. Elmasry (auth.), Mohamed I. Elmasry (eds.)


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