Noise-Boosted Backpropagation Learning of Feedforward Threshold Neural Networks for Function Approximation

2021 ◽  
Vol 70 ◽  
pp. 1-12
Author(s):  
Lingling Duan ◽  
Fabing Duan ◽  
Francois Chapeau-Blondeau ◽  
Derek Abbott
Keyword(s):  
Neural Networks ◽  
Function Approximation ◽  
Backpropagation Learning

scholarly journals Neural Network Programming in Python

2019 ◽  
Vol 8 (6S4) ◽  
pp. 373-377
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Programming Language ◽  
Function Approximation ◽  
Learning Rule ◽  
Network Programming ◽  
Short Introduction ◽  
Python Programming Language ◽  
Python Programming ◽  
Backpropagation Learning

In this paper a basic introduction to neural networks is made. An emphasis is given on a two layer perceptron used extensively for function approximation. The backpropagation learning rule is than briefly introduced. A short introduction into Python programming language is made and a program for the perceptron design is written and discussed in some detail. The “neurolab” library is used for this purpose.

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