Qualitative Analysis of Continuous Complex-Valued Associative Memories
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
On activation functions for complex-valued neural networks: existence of energy functions
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Complex-valued multistate neural associative memory
IEEE Transactions on Neural Networks
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
| Hi-index | 0.00 |
Associative memories are one of the popular applications of neural networks and several studies on their extension to the complex domain have been done. One of the important factors to characterize behavior of a complex-valued neural network is its activation function which is a nonlinear complex function. We have already proposed a model of self-correlation type associative memories using complex-valued neural networks with one of the most commonly used activation function. In this paper, we propose two additional models using different nonlinear complex functions and investigated their behaviors as associative memories theoretically. Comparisons are also made among these three models in terms of dynamics and storage capabilities.