Recursive Orthogonal Least Squares Learning with Automatic Weight Selection for Gaussian Neural Networks Meng H. Fun, [removed], Oklahoma State University Martin T. Hagan, [removed], Oklahoma S

First Page		Document Content
Date: 2008-01-23 11:12:51 Interpolation Numerical analysis Computational statistics Radial basis function network Numerical linear algebra Radial basis function Recursive least squares filter Gaussian function Orthogonal matrix Mathematics Neural networks Statistics		Recursive Orthogonal Least Squares Learning with Automatic Weight Selection for Gaussian Neural Networks Meng H. Fun, [removed], Oklahoma State University Martin T. Hagan, [removed], Oklahoma S Add to Reading List Source URL: hagan.ecen.ceat.okstate.edu Download Document from Source Website File Size: 251,62 KB Share Document on Facebook

	3 May 1998 ITERATED RANDOM FUNCTIONS Persi Diaconis Department of Mathematics & ORIE Cornell University DocID: 1xVWv - View Document
	SCAN 2018 Post-conference Proceedings Special Issue of Journal of Computational and Applied Mathematics Call for Papers Special Issue on the 18th International Symposium on Scientific Computing, Computer Arithmetic, DocID: 1xVSx - View Document
	MATHEMATICS OF COMPUTATION Volume 00, Number 0, Pages 000–000 SXXBETTER POLYNOMIALS FOR GNFS SHI BAI, CYRIL BOUVIER, ALEXANDER KRUPPA, AND PAUL ZIMMERMANN DocID: 1xVRE - View Document
	A characterization of Riemann integrability Cosmin Burtea Faculty of Mathematics, "Al. I. Cuza" University of Ia³i, Romania Abstract We prove a characterization of Riemann integrability by using some Darboux-like sums w DocID: 1xVOd - View Document
	Mathematics 7-12, BS "DBEFNJD.BQ 5IF"DBEFNJD.BQTFSWFTBTBTVHHFTUFEDPVSTFTFRVFODFPOMZ4UVEFOUTBSFOPUMJNJUFEUPUIJTQMBOJUJTNFBOUUPCFVTFEBT DocID: 1xVH0 - View Document