A Bidirectional Hetero-Associative Memory for True-Color Patterns
Neural Processing Letters
A New Associative Model with Dynamical Synapses
Neural Processing Letters
IEEE Transactions on Neural Networks
Complex-valued neural networks: the merits and their origins
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
An iterative learning scheme for multistate complex-valued and quaternionic hopfield neural networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Large-scale pattern storage and retrieval using generalized brain-state-in-a-box neural networks
IEEE Transactions on Neural Networks
Permutation-based finite implicative fuzzy associative memories
Information Sciences: an International Journal
Recent progress in applications of complex-valued neural networks
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Dynamic complex-valued associative memory with strong bias terms
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
Nonlinear quantization on Hebbian-type associative memories
Applied Intelligence
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In this letter, new design methods for the complex-valued multistate Hopfield associative memories (CVHAMs) are presented. We show that the well-known projection rule proposed by Personnaz can be generalized to complex domain such that the weight matrix of the CVHAM can be designed by using a simple and effective method. The stability of the proposed CVHAM is analyzed by using energy function approach which shows that in synchronous update mode the proposed model is guaranteed to converge to a fixed point from any given initial state. Moreover, the projection geometry of the generalized projection rule (GPR) is discussed. In order to enhance the recall capability, a strategy of eliminating the spurious memories is also reported. The validity and the performance of the proposed methods are investigated by computer simulation