Discrete Hopfield neural network associative memor
2016-08-23
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In everyday life, often encounter the noisy character recognition, such as car number and car number plates in the transport system, in the car, to withstand the weather for the natural environment, creating fonts blurry, illegible. How to grab complete information from such incomplete characters, is the key to character recognition problem. As part of character recognition number identified in the management of postal, transportation and commercial paper has a very high value. There are many methods for character recognition, is divided into recognition, probabilistic identification of neural network and fuzzy recognition and so on. Traditional digital recognition in a disturbing number of cases unable to identify discrete Hopfield neural network associative memory and optimal functionality, and the convergence of computing speed. This case study identification numbers using its features, and the introduction of interference, through simulation experiment design of network digital noi
matlab
神经网络
识别
hopfield
联想
数字
离散
记忆
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