DocumentCode
288641
Title
Reducing the effect of quantization by weight scaling
Author
Withagen, Heini
Author_Institution
Dept. of Electr. Eng., Eindhoven Univ. of Technol., Netherlands
Volume
4
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
2128
Abstract
By a statistical analysis of the behaviour of feedforward neural networks to errors in the weights, we show that an optimal scaling factor for the weights exists when the number of inputs to a neuron increases. When this scaling technique is used, the error in the output of a neuron due to quantization errors is not influenced by the size of the network anymore. This technique is especially interesting for the implementation of neural networks using analog electronics
Keywords
feedforward neural nets; roundoff errors; statistical analysis; feedforward neural networks; optimal scaling factor; quantization errors; statistical analysis; weight scaling; Artificial neural networks; Feedforward neural networks; Multi-layer neural network; Neural network hardware; Neural networks; Neurons; Quantization; Signal to noise ratio; Statistical analysis; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374544
Filename
374544
Link To Document