Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Fuzzy engineering
Handbook of Computer Vision Algorithms in Image Algebra
Handbook of Computer Vision Algorithms in Image Algebra
Generalizing Operations of Binary Autoassociative Morphological Memories Using Fuzzy Set Theory
Journal of Mathematical Imaging and Vision
Reconstruction of Patterns from Noisy Inputs Using Morphological Associative Memories
Journal of Mathematical Imaging and Vision
Associative morphological memories based on variations of the kernel and dual kernel methods
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
IEEE Transactions on Computers
Morphological associative memories
IEEE Transactions on Neural Networks
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Autoassociative morphological memories (AMMs) are a class of artificial feedforward neural networks whose computation at each neurode is based on lattice algebra. In a similar way as the classic correlation encoding used for binary patterns in linear associative memories or recurrent content addressable memories such as the Hopfield network, storage and recall in AMMs is also realized using matrix transforms which in the present case correspond to minimax matrix operations. This paper describes an enhanced fuzzy autoassociative morphological memory that couples a fuzzy AMM to a Hamming network that increases the capability of perfect recalls from noisy binary inputs.