Analysis of Hopfield Autoassociative Memory in the Character Recognition
Journal Title: International Journal on Computer Science and Engineering - Year 2010, Vol 2, Issue 3
Abstract
This paper aims that analyzing neural network method in attern recognition. A neural network is a processing device, hose design was inspired by the design and functioning of uman brain and their components. The proposed solutions focus on applying Hopfield Autoassociative memory model for pattern recognition. The Hopfield network is an ssociative memory. he primary function of which is to retrieve in a pattern stored in memory, when an incomplete or noisy version of that pattern is resented. An associative emory is a storehouse of associated patterns that are encoded in some form. In auto-association, n input pattern is associated with itself and the states of nput and output units coincide. When the storehouse is incited with given distorted or partial pattern, the associated pattern pair stored in its perfect form is recalled. Pattern recognition echniques are associated a symbolic identity with the image f he pattern. This problem of replication of patterns by machines (computers) involves the machine printed patterns. here is no idle memory containing data and programmed, but each neuron is programmed and continuously active.
Authors and Affiliations
Yash Pal Singh, , Abhilash Khare , Amit gupta
Keywords
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