𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Evaluation of neural network performance and generalisation using thresholding functions

✍ Scribed by S. G. Pierce; K. Worden; G. Manson


Publisher
Springer-Verlag
Year
2006
Tongue
English
Weight
701 KB
Volume
16
Category
Article
ISSN
0941-0643

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Analysis of neural network energy functi
✍ Masanori Izumida; Kenji Murakami; Tsunehiro Aibara πŸ“‚ Article πŸ“… 1992 πŸ› John Wiley and Sons 🌐 English βš– 782 KB

## Abstract In this paper, we discuss a method for analyzing the energy function of a Hopfield‐type neural network. In order to analyze the energy function which solves the given minimization problem, or simply, the problem, we define the standard form of the energy function. In general, a multidim

Properties and performance of orthogonal
✍ Chieh F. Sher; Ching-Shiow Tseng; Chen-San Chen πŸ“‚ Article πŸ“… 2001 πŸ› John Wiley and Sons 🌐 English βš– 216 KB

Backpropagation neural network has been applied successfully to solving uncertain problems in many fields. However, unsolved drawbacks still exist such as the problems of local minimum, slow convergence speed, and the determination of initial weights and the number of processing elements. In this pa

Predicting LDC debt rescheduling: perfor
✍ Douglas K. Barney; Janardhanan A. Alse πŸ“‚ Article πŸ“… 2001 πŸ› John Wiley and Sons 🌐 English βš– 150 KB

## Abstract Empirical studies in the area of sovereign debt have used statistical models singularly to predict the probability of debt rescheduling. Unfortunately, researchers have made few efforts to test the reliability of these model predictions or to identify a superior prediction model among c