DocumentCode :
820935
Title :
Statistically controlled activation weight initialization (SCAWI)
Author :
Drago, Gian Paolo ; Ridella, Sandro
Author_Institution :
Istituto per i Circuiti Elettronici, CNR, Genova, Italy
Volume :
3
Issue :
4
fYear :
1992
fDate :
7/1/1992 12:00:00 AM
Firstpage :
627
Lastpage :
631
Abstract :
An optimum weight initialization which strongly improves the performance of the back propagation (BP) algorithm is suggested. By statistical analysis, the scale factor, R (which is proportional to the maximum magnitude of the weights), is obtained as a function of the paralyzed neuron percentage (PNP). Also, by computer simulation, the performances on the convergence speed have been related to PNP. An optimum range for R is shown to exist in order to minimize the time needed to reach the minimum of the cost function. Normalization factors are properly defined, which leads to a distribution of the activations independent of the neurons, and to a single nondimensional quantity, R, the value of which can be quickly found by computer simulation
Keywords :
convergence of numerical methods; minimisation; neural nets; statistical analysis; backpropagation; convergence; cost function; neural nets; optimisation; paralyzed neuron percentage; scale factor; statistically controlled activation weight initialisation; Application software; Computer simulation; Convergence; Cost function; Feedforward neural networks; Neural networks; Neurons; Statistical analysis; Testing; Weight control;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.143378
Filename :
143378
Link To Document :
بازگشت