Abstract
A design method of associative memory model with expecting fault-tolerant field is proposed.The benefit of this method is to make the designed associative memory model memory sample fault-tolerant field which implements the hoped situation. For any different P samples in n dimensional binary information space D n = [1, − 1]n and any the p compartmentalization C 1,C 2,...,C p of D n, an associative memory model with expecting fault-tolerant field C 1,C 2,...,C p can be designed by the method. The method better solves the difficult synthesis problems of associative memory models.
Supported by the National Natural Foundation of China No.60673101 and 863 Project of China (No.2006AA04Z110, 2006AA01Z123).
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References
Yang, G.: Models of Artificial Life. Science Press, Beijing (2005)
Tu, X., et al.: Theory of Biologic Control. Science Press, Beijing (1980)
Lee, D., Wang, W.: A Multivalued Bidirectional Associative Memory Operating on a Complex Domain. Neural Networks 11, 1623–1635 (1998)
Wu, Y., Pados, D.A.: A Feedforward Bidirectional Associative Memory. IEEE Transactions on Neural Networks 4, 859–866 (2000)
Wu, Y., Batalama, S.N.: An Efficient Learning Algorithm for Associative Memories. IEEE Transactions on Neural Networks 5, 1058–1066 (2000)
Wu, Y., Batalama, S.N.: Improved One-shot Learning for Feedforward Associative Memories with Application to Composite Pattern Association. IEEE Transactions on Systems, Man and Cybernetics, Part B 1, 119–125 (2001)
Chang, J., Cho, C.: Second-order Asymmetric BAM Design with a Maximal Basin of Attraction. IEEE Transactions on Systems, Man and Cybernetics, Part A 4, 421–428 (2003)
Kamio, T., Morisue, M.: A Synthesis Procedure for Associative Memories Using Cellular Neural Networks with Space-invariant Cloning Template Library. In: Proceedings of the International Joint Conference on Neural Networks, vol. 2, pp. 885–890 (2003)
Costantini, G., Casali, D., Perfetti, R.: Neural Associative Memory Storing Gray-coded Gray-scale Images. IEEE Transactions on Neural Networks 3, 703–707 (2003)
Muezzinoglu, M.K., Guzelis, C., Zurada, J.M.: A New Design Method for the Complex-Valued Multistate Hopfield Associative Memory. IEEE Transactions on Neural Networks 4, 891–899 (2003)
Muezzinoglu, M.K., Guzelis, C.: A Boolean Hebb Rule for Binary Associative Memory Design. IEEE Transactions on Neural Networks 1, 195–220 (2004)
Zhang, L., Wu, F., Zhang, B., Han, J.: Study of Multilayer Feedforword Neural Network and Synthetic Algorithm. Journal of software 7, 440–448 (1995)
Liang, X., Wu, L., Yu, J.: An Effective Learning Algorithm of Associative Memory Neural Network. Journal of automation 6, 721–727 (1997)
Zhang, D., Chen, S.: The Expanding Mult-value Index Bi-directional Associative Memory Model and Application. Journal of software 3, 97–702 (2002)
Tao, Q., Cao, J., Sun, D.: Associative Memory Neural Network Model Base on Linear Programming. Journal of computer 4, 377–381 (2001)
Wei, H.: The Autoassociate Memory Model of Auto-mapping Base on Structure Learning and Iterating. Journal of software 3, 438–446 (2002)
Yang, G., Tu, X., Wang, S.: A Time-Varying Fault-Tolerant Field Perceptive Associative Memory Model and the Realization Algorithms. Chinese Journal of Computers 3, 431–440 (2006)
Tu, X.: Artificial Fish -a Way of Artificial Life of the Computer Animation. Qinghua University Press, Beijing (2001)
Wang, S., Chen, X., Zeng, Y., et al.: In General Neural Network Hardware Neuron Basic Mathematical Model Discussion. Journal of electronics 5, 577 (2001)
Huang, D.: Theory of Neuron Network Mode Recognition System. Publishing House of Electronics Industry, Beijing (1996)
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Yang, G., Wang, S., Yan, Q. (2007). A Design Method of Associative Memory Model with Expecting Fault-Tolerant Field. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72395-0_76
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DOI: https://doi.org/10.1007/978-3-540-72395-0_76
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