Retrieval performance of Hopfield Associative Memory with Complex-valued and Real-valued neurons

In this paper, we propose a Hopfield Associative Memory with Complex-valued and Real-valued neurons (CRHAM). CRHAM is an associative memory which can perform storing and recalling multi-valued patterns. A part of neurons in the network are complex-valued neurons, and the rest of neurons are conventional (real-valued) neurons. Spurious patterns that degrade the retrieval performance can be reduced by the combination of those two types of neurons. The experimental results show that high robustness for noisy inputs is achieved by CRHAM as compared with conventional complex-valued associative memories, such as Complex-valued Hopfield Associative Memory (CHAM) and Complex-valued Bipartite Auto-Associative Memory (CBAAM).

[1]  Masaki Kobayashi,et al.  Pseudo-Relaxation Learning Algorithm for Complex-Valued Associative Memory , 2008, Int. J. Neural Syst..

[2]  Jacek M. Zurada,et al.  Complex-valued multistate neural associative memory , 1996, IEEE Trans. Neural Networks.

[3]  Naum N. Aizenberg,et al.  CNN based on multi-valued neuron as a model of associative memory for grey scale images , 1992, CNNA '92 Proceedings Second International Workshop on Cellular Neural Networks and Their Applications.

[4]  Jacek M. Zurada,et al.  A new design method for the complex-valued multistate Hopfield associative memory , 2003, IEEE Trans. Neural Networks.

[5]  D.-L. Lee,et al.  Improvements of Complex-Valued Hopfield Associative Memory by Using Generalized Projection Rules , 2006, IEEE Transactions on Neural Networks.

[6]  Masaki Kobayashi,et al.  Complex-valued bidirectional auto-associative memory , 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

[7]  Gouhei Tanaka,et al.  Complex-valued multistate associative memory with nonlinear multilevel functions for gray-level image reconstruction , 2009, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

[8]  B Kosko,et al.  Adaptive bidirectional associative memories. , 1987, Applied optics.

[9]  Masaki Kobayashi,et al.  Complex-Valued Bipartite Auto-Associative Memory , 2014, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences.

[10]  Wen-June Wang,et al.  A multivalued bidirectional associative memory operating on a complex domain , 1998, Neural Networks.

[11]  Yukio Kosugi,et al.  An image storage system using complex-valued associative memories , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[12]  Noest.  Discrete-state phasor neural networks. , 1988, Physical review. A, General physics.

[13]  H. Aoki.  Image Association Using a Complex-Valued Associative Memory Model , 2000 .

[14]  BART KOSKO,et al.  Bidirectional associative memories , 1988, IEEE Trans. Syst. Man Cybern..

[15]  Yuko Osana,et al.  Chaotic Complex-Valued Bidirectional Associative Memory , 2009, 2009 International Joint Conference on Neural Networks.