NDLI: Approximating Gaussian Mixture Model or Radial Basis Function Network With Multilayer Perceptron

Content Provider	IEEE Xplore Digital Library
Author	Patrikar, A.M.
Copyright Year	2012
Abstract	Gaussian mixture models (GMMs) and multilayer perceptron (MLP) are both popular pattern classification techniques. This brief shows that a multilayer perceptron with quadratic inputs (MLPQ) can accurately approximate GMMs with diagonal covariance matrices. The mapping equations between the parameters of GMM and the weights of MLPQ are presented. A similar approach is applied to radial basis function networks (RBFNs) to show that RBFNs with Gaussian basis functions and Euclidean norm can be approximated accurately with MLPQ. The mapping equations between RBFN and MLPQ weights are presented. There are well-established training procedures for GMMs, such as the expectation maximization (EM) algorithm. The GMM parameters obtained by the EM algorithm can be used to generate a set of initial weights of MLPQ. Similarly, a trained RBFN can be used to generate a set of initial weights of MLPQ. MLPQ training can be continued further with gradient-descent based methods, which can lead to improvement in performance compared to the GMM or RBFN from which it is initialized. Thus, the MLPQ can always perform as well as or better than the GMM or RBFN.
Page Count	6
File Size	472121
Starting Page	1161
Ending Page	1166
File Format	PDF
ISSN	2162237X
Volume Number	24
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	radial basis function networks (RBFNs) Artificial neural networks hidden Markov models (HMMs) multilayer perceptron (MLP)
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Computer Science Applications Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Plane-Gaussian artificial neural network

A review of genetic algorithms applied to training radial basis function networks

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis

Damage detection in Timoshenko beam structures by multilayer perceptron and radial basis function networks

Learning criteria for training neural network classifiers

Exchange rate forecasting: comparison of various architectures of neural networks

Contingency evaluation and monitorization using artificial neural networks

MLP/RBF neural-networks-based online global model identification of synchronous generator

An adaptive local linear optimized radial basis functional neural network model for financial time series prediction

Approximating Gaussian Mixture Model or Radial Basis Function Network With Multilayer Perceptron

Similar Documents

Plane-Gaussian artificial neural network

A review of genetic algorithms applied to training radial basis function networks

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis

Damage detection in Timoshenko beam structures by multilayer perceptron and radial basis function networks

Learning criteria for training neural network classifiers

Exchange rate forecasting: comparison of various architectures of neural networks

Contingency evaluation and monitorization using artificial neural networks

MLP/RBF neural-networks-based online global model identification of synchronous generator

An adaptive local linear optimized radial basis functional neural network model for financial time series prediction

Approximating Gaussian Mixture Model or Radial Basis Function Network With Multilayer Perceptron