𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A comparison study of binary feedforward neural networks and digital circuits

✍ Scribed by Hubertus M.A. Andree; Gerard T. Barkema; Wim Lourens; Arie Taal; Jos C. Vermeulen

Publisher
Elsevier Science
Year
1993
Tongue
English
Weight
411 KB
Volume
6
Category
Article
ISSN
0893-6080

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Classes of feedforward neural networks a
Classes of feedforward neural networks and their circuit complexity
✍ John S. Shawe-Taylor; Martin H.G. Anthony; Walter Kern πŸ“‚ Article πŸ“… 1992 πŸ› Elsevier Science 🌐 English βš– 594 KB

Th& paper aims to p&ce neural networks in the conte.\t ol'booh'an citz'ldt complexit.l: 1,1~, de/itte aplm~priate classes qlfeedybrward neural networks with specified fan-in, accm'ac)' olcomputation and depth and ttsing techniques" o./commzmication comph:Β₯ity proceed to show t/tat the classes.fit in

Comparison study of pattern-synthesis te
Comparison study of pattern-synthesis techniques using neural networks
✍ R. Shavit; I. Taig πŸ“‚ Article πŸ“… 2004 πŸ› John Wiley and Sons 🌐 English βš– 242 KB

## Abstract In this paper, a comparison study among three neural‐network algorithms for the synthesis of array patterns is presented. The neural networks are used to estimate the array elements' excitations for an arbitrary pattern. The architecture of the neural networks is discussed and simulatio

Universal Approximation Using Feedforwar
Universal Approximation Using Feedforward Neural Networks: A Survey of Some Existing Methods, and Some New Results
✍ Franco Scarselli; Ah Chung Tsoi πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 699 KB

In this paper, we present a review of some recent works on approximation by feedforward neural networks. A particular emphasis is placed on the computational aspects of the problem, i.e. we discuss the possibility of realizing a feedforward neural network which achieves a prescribed degree of accura