Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
The stability problem for fuzzy bidirectional associative memories
Fuzzy Sets and Systems - Possibility theory and fuzzy logic
Detecting Pedestrian Abnormal Behavior Based on Fuzzy Associative Memory
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 06
Research on Properties of Max-Product Fuzzy Associative Memory Networks
ISDA '08 Proceedings of the 2008 Eighth International Conference on Intelligent Systems Design and Applications - Volume 02
On fuzzy associative memory with multiple-rule storage capacity
IEEE Transactions on Fuzzy Systems
On new fuzzy morphological associative memories
IEEE Transactions on Fuzzy Systems
Implicative Fuzzy Associative Memories
IEEE Transactions on Fuzzy Systems
Morphological associative memories
IEEE Transactions on Neural Networks
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FAM is an Associative Memory that uses operators of Fuzzy Logic and Mathematical Morphology (MM). FAMs possess important advantages including noise tolerance, unlimited storage, and one pass convergence. An important property, deciding FAM performance, is the ability to capture contents of each pattern, and associations of patterns. Standard FAMs capture either contents or associations of patterns well, but not both of them. In this paper, we propose a novel FAM that effectively stores both contents and associations of patterns. We improve both learning and recalling processes of FAM. In learning process, the associations and contents are stored by mean of input and output patterns and they are generalised by erosion operator. In recalling process, a new threshold is added to output function to improve outputs. Experiments show that noise tolerance of the proposed FAM is better than standard FAMs with different types of noise.