文章基本信息

标题：Analysis of Hopfield Autoassociative Memory in the Character Recognition
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作者：Yash Pal Singh ; Abhilash Khare ; Amit Gupta 等
期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2010
卷号：2
期号：3
页码：500-503
出版社：Engg Journals Publications
摘要：This paper aims that analyzing neural network method in pattern recognition. A neural network is a processing device, whose design was inspired by the design and functioning of human brain and their components. The proposed solutions focus on applying Hopfield Autoassociative memory model for pattern recognition. The Hopfield network is an associative memory. The primary function of which is to retrieve in a pattern stored in memory, when an incomplete or noisy version of that pattern is presented. An associative memory is a storehouse of associated patterns that are encoded in some form. In auto-association, an input pattern is associated with itself and the states of input and output units coincide. When the storehouse is incited with a given distorted or partial pattern, the associated pattern pair stored in its perfect form is recalled. Pattern recognition techniques are associated a symbolic identity with the image of the pattern. This problem of replication of patterns by machines (computers) involves the machine printed patterns. There is no idle memory containing data and programmed, but each neuron is programmed and continuously active.
关键词：Neural network; machine printed character; pattern recognition.