𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Stochastic neural networks with the weighted Hebb rule

✍ Scribed by Caren Marzban; Raju Viswanathan

Publisher
Elsevier Science
Year
1994
Tongue
English
Weight
501 KB
Volume
191
Category
Article
ISSN
0375-9601

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Reformulated radial basis function neura
Reformulated radial basis function neural networks with adjustable weighted norms
✍ Mary M. Randolph-Gips; Nicolaos B. Karayiannis πŸ“‚ Article πŸ“… 2003 πŸ› John Wiley and Sons 🌐 English βš– 201 KB

This article presents a new family of reformulated radial basis function (RBF) neural networks that employ adjustable weighted norms to measure the distance between the training vectors and the centers of the radial basis functions. The reformulated RBF model introduced in this article incorporates

Fuzzy neural network with fuzzy signals
Fuzzy neural network with fuzzy signals and weights
✍ Yoichi Hayashi; James J. Buckley; Ernest Czogala πŸ“‚ Article πŸ“… 1993 πŸ› John Wiley and Sons 🌐 English βš– 534 KB

We discuss the direct fuzzification of a standard layered, feedforward, neural network where the signals and weights are fuzzy sets. A fuzzified delta rule is presented for learning. Three applications are given including fuzzy expert systems, fuzzy hierarchical analysis, and fuzzy systems modeling.

Revisiting Hume-Rothery’s Rules with art
Revisiting Hume-Rothery’s Rules with artificial neural networks
✍ Y.M. Zhang; S. Yang; J.R.G. Evans πŸ“‚ Article πŸ“… 2008 πŸ› Elsevier Science 🌐 English βš– 262 KB

Hume-Rothery's breadth of knowledge combined with a quest for generality gave him insights into the reasons for solubility in metallic systems that have become known as Hume-Rothery's Rules. Presented with solubility details from similar sets of constitutional diagrams, can one expect artificial neu