Title :
Neuro-Fuzzy Function Approximations Using Feedforward Networks - An Application of Sigmoidal Signal
Author :
Kumar, V. Suresh ; Chandra, S. Vijaya ; Kumar, C. Susil
Author_Institution :
Dept. of Comput. Sci. & Eng., Velammal Coll. of Eng. & Technol., Madurai, India
Abstract :
Chen, Cybenko, Funahashi, Babri, Gorban, Barron and others studied function approximation capabilities by feed forward neural networks. Ramakrishnan and his collaborators introduced the left sigmoidal and right sigmoidal signals to prove some function approximation theorems in continuous functions. In this paper, the right sigmoidal signal is used to establish function approximation theorems using infimum and supremum operators.
Keywords :
feedforward neural nets; function approximation; fuzzy set theory; feedforward neural networks; infimum operators; neuro fuzzy function approximations; sigmoidal signal; supremum operators; Artificial neural networks; Feedforward neural networks; Function approximation; Fuzzy systems; Neurons; Nonhomogeneous media; Sigmoidal signal; feedforward networks; function approximation; fuzzy set; neuro-fuzzy systems etc.;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-9211-4
DOI :
10.1109/ICMLA.2010.140
