In this paper, we extend the neural network for implementing fuzzy relation systems based on sup −t composition in [5] to min-implication composition. We.
In this paper, fuzzy associative memories with perfect recall are constructed, and new on-line learning algorithms adapting the weights of its interconnections ...
Min-implication fuzzy relation equations based on Boolean-type implications can also be viewed as a way of implementing fuzzy associative memories with ...
Oct 22, 2024 · New Algorithms of Neural Fuzzy Relation Systems with Min-implication Composition. Conference Paper. Full-text available. Feb 2005; Lect Notes ...
A new algorithm is proposed to solve the fuzzy relation equation P∘Q=R with max–min composition and max–product composition.
Missing: implication | Show results with:implication
New Algorithms of Neural Fuzzy Relation Systems with Min-implication Composition · Fuzzy relation equations and fuzzy inference systems: an inside approach.
In this paper, a neural network model is proposed in order to represent fuzzy relational systems without the need of the construction of the fuzzy relation ...
Missing: implication | Show results with:implication
New Algorithms of Neural Fuzzy Relation Systems with Min-implication Composition ... An Efficient Algorithm to Computing Max–Min Inverse Fuzzy Relation for ...
Analytical methods are proposed for solving fuzzy linear system of equations when the composition is max-product. These methods provide universal algorithm for ...
A fuzzy mapping rule describes a functional mapping relationship between inputs and an output using linguistic terms, while a fuzzy implication rule describes a ...