DocumentCode
3617508
Title
Visual comparison of performance for different activation functions in MLP networks
Author
F. Piekniewski;L. Rybicki
Author_Institution
Fac. of Math. & Comput. Sci., Nicolaus Copernicus Univ., Torun, Poland
Volume
4
fYear
2004
fDate
6/26/1905 12:00:00 AM
Firstpage
2947
Abstract
Multi layer perceptron networks have been successful in many applications, yet there are many unsolved problems in the theory. Commonly, sigmoidal activation functions have been used, giving good results. The backpropagation algorithm might work with any other activation function on one condition though - it has to have a differential. We investigate some possible activation functions and compare the results they give on some sample data sets.
Keywords
"Intelligent networks","Transfer functions","Neurons","Neural networks","Mathematics","Computer science","Electronic mail","Logistics","Application software","Interpolation"
Publisher
ieee
Conference_Titel
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-8359-1
Type
conf
DOI
10.1109/IJCNN.2004.1381133
Filename
1381133
Link To Document