Normalized Incremental Subgradient Algorithm and Its Application

The problem of minimizing the sum of a number of component functions is of great importance in the real world. In this paper, a new incremental optimization algorithm, named normalized incremental subgradient (NIS) algorithm, is proposed for a class of such problems where the component functions hav...

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Bibliographic Details
Published in:	IEEE transactions on signal processing Vol. 57; no. 10; pp. 3759 - 3774
Main Authors:	Shi, Qingjiang, He, Chen, Jiang, Lingge
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.10.2009 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Applied sciences Bandwidth Convergence Convex feasibility problem Detection, estimation, filtering, equalization, prediction distributed maximum likelihood estimation Energy measurement Exact sciences and technology Feasibility Information, signal and communications theory Iterative algorithms Localization Mathematical analysis Mathematical models Maximum likelihood estimation Minima Miscellaneous node localization normalized incremental subgradient algorithm Optimization Optimization methods Particle measurements Signal and communications theory Signal processing Signal processing algorithms Signal, noise source localization Studies Telecommunications and information theory wireless sensor network Wireless sensor networks Performance evaluation Wireless telecommunication Gauss Newton method wireless sensor network Updating Algorithm Implementation Optimization Remote sensing normalized incremental subgradient algorithm Convex feasibility problem Source localization Signal processing Wireless network Numerical simulation Feasibility node localization Maximum likelihood Sensor array distributed maximum likelihood estimation Target detection Signal detection
ISSN:	1053-587X, 1941-0476
Online Access:	Get full text
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