DocumentCode
1946322
Title
A Functional Link Network With Ordered Basis Functions
Author
Sureka, Saurabh ; Manry, Michael
Author_Institution
Univ. of Texas at Arlington, Arlington
fYear
2007
fDate
12-17 Aug. 2007
Firstpage
1708
Lastpage
1713
Abstract
A procedure is presented for selecting and ordering the polynomial basis functions in the functional link net (FLN). This procedure, based upon a modified Gram Schmidt orthonormalization, eliminates linearly dependent and less useful basis functions at an early stage, reducing the possibility of combinatorial explosion. The number of passes through the training data is minimized through the use of correlations. A one-pass method is used for validation and network sizing. Function approximation and learning examples are presented. Results for the ordered FLN are compared with those for the FLN, group method of data handling, and multi-layer perceptron.
Keywords
radial basis function networks; functional link network; modified Gram Schmidt orthonormalization; one-pass method; polynomial basis function; Chebyshev approximation; Data handling; Explosions; Function approximation; Least squares approximation; Neural networks; Polynomials; Strontium; Training data; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location
Orlando, FL
ISSN
1098-7576
Print_ISBN
978-1-4244-1379-9
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2007.4371215
Filename
4371215
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