¡¡Chinese Journal of Computers   Full Text
  TitleA Design Method of Ahead Masking Associative Memory Model with Expecting Fault-Tolerant Field
  AuthorsYANG Guo-Wei1),2) WANG Shou-Jue2) LI Wei-Jun2)
  Address1)(College of Automation Engineering, Qingdao University, Qingdao, Shandong 266071)
2)(Laboratory of Artificial Neural Network, Institute of Semiconductors£¬ Chinese Academy of Sciences£¬ Beijing 100083)
  Year2009
  IssueNo.1(124¡ª131)
  Abstract &
  Background 		Abstract The synthesis problems of associative memory models are not better solved until now. A design method of ahead masking associative memory model with expecting fault-tolerant field is proposed by use of the general feed-forward network and sequential learning algorithm given by authors. The method better solves the difficult synthesis problems of associative memory models. The ahead masking associative memory model designed by the method have any expecting fault-tolerant fields about the samples.
Keywords neural network; associative memory; fault-tolerant field; model; design
Background The paper studies the synthesis problems of associative memory models. Many results about synthesis and analysis of associative memory have been obtained, but the synthesis problems of associative memory models are not better solved until now. In this paper, a design method of ahead masking associative memory model with expecting fault-tolerant field is proposed by use of the general feed-forward network and sequential learning algorithm given by authors. The method better solves the difficult synthesis problems of associative memory models.
¡°A Design Method of Ahead Masking Associative Memory Model with Expecting Fault-Tolerant Field¡± is a subsidiary one of the project ¡°Study on New Neural Network Models of Information Processing of Artificial Brain¡± sponsored by National Nature Science Foundation of China. The major research interests of this group are artificial intelligence, artificial life and artificial neural network, and so on. In the project, the authors have proposed many neural network models of artificial life for information processing, especially associative memory models, and then improved some existing information processing neural network models of artificial life. Most of the works can be found in book ¡°Yang Guo-Wei. Models of Artificail Life. Beijing: Science Press, 2005¡±.