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About 10,000 papers for “Basis function”

basis function

2008

Citation: 'basis function' in the IUPAC Compendium of Chemical Terminology, 3rd ed.; International Union of Pure and Applied Chemistry; 2006. Online version 3.0.1, 2019. 10.1351/goldbook.BT06998 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.

Cited by 0

Basis Function

Владимир И. Минкин · IUPAC Standards Online · 2016

The glossary contains definitions and explanatory notes for more than 450 terms used in the context of multidisciplinary research and publications related to applications of modern theoretical concepts, computational and graph-theoretical methods to investigation into structure, reactivity, spectroscopic and other physical and physicochemical properties of organic, organometallic and metal coordination compounds. The aim of the glossary is to provide guidance on terminology used in theoretical organic chemistry and to contribute to the elimination of inconsistencies and ambiguities in the meanings of terms in the area.

Cited by 0

Radial‐Basis Function Networks

2016

This chapter focuses on the radial-basis function (RBF) network as an alternative to multilayer perceptrons. It will be interesting to find that in a multilayer perceptron, the function approximation is defined by a nested set of weighted summations, while in a RBF network, the approximation is defined by a single weighted sum. The chapter focuses on the use of a Gaussian function as the radial-basis function. The reason behind the choice of the Gaussian function as the radial-basis function in building RBF networks is that it has many desirable properties, which will become evident as the discussion progresses. It is important to point out that RBF networks and multilayer perceptrons can be trained in alternative ways besides those presented. For multilayer perceptrons, the backpropagation algorithm is simple to compute locally and it performs stochastic gradient descent in weight space when the algorithm is implemented in an online learning mode.

Cited by 0

Radial-Basis-Function Networks

Åge J. Eide, Thomas Lindblad, Guy Paillet · ˜The œelectrical engineering handbook/Electrical engineering handbook series/Electrical engineering handbook · 2011

Cited by 2

Radial Basis Function Networks

Andries P. Engelbrecht · 2007

This chapter contains sections titled: Learning Vector Quantizer-II Radial Basis Function Neural Networks Assignments

Cited by 8

Heterogeneous Radial Basis Function

Byu Scholarsarchive, Tony R. Martinez, D. Randall Wilson et al. · 1996

This Peer-Reviewed Article is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in All Faculty

Cited by 0