Solving variational inequalities using wavelet methods

Markus Hegland; Dale Roberts

Solving variational inequalities using wavelet methods

Markus Hegland^*, Dale Roberts

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

We present a multiscale (or hierarchical) approximation of elliptic variational inequalities where there is no need to develop an explicit mesh refinement strategy. That is, we use wavelets to recast elliptic variational inequalities as constrained quadratic optimisation problems in l2 which we solve with the primal dual-path following method and the projected gradient algorithm.

Original language	English
Pages (from-to)	C949-C966
Journal	ANZIAM Journal
Volume	52
Publication status	Published - 2010

Cite this

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title = "Solving variational inequalities using wavelet methods",

abstract = "We present a multiscale (or hierarchical) approximation of elliptic variational inequalities where there is no need to develop an explicit mesh refinement strategy. That is, we use wavelets to recast elliptic variational inequalities as constrained quadratic optimisation problems in l2 which we solve with the primal dual-path following method and the projected gradient algorithm.",

author = "Markus Hegland and Dale Roberts",

year = "2010",

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pages = "C949--C966",

journal = "ANZIAM Journal",

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T1 - Solving variational inequalities using wavelet methods

AU - Hegland, Markus

AU - Roberts, Dale

PY - 2010

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N2 - We present a multiscale (or hierarchical) approximation of elliptic variational inequalities where there is no need to develop an explicit mesh refinement strategy. That is, we use wavelets to recast elliptic variational inequalities as constrained quadratic optimisation problems in l2 which we solve with the primal dual-path following method and the projected gradient algorithm.

AB - We present a multiscale (or hierarchical) approximation of elliptic variational inequalities where there is no need to develop an explicit mesh refinement strategy. That is, we use wavelets to recast elliptic variational inequalities as constrained quadratic optimisation problems in l2 which we solve with the primal dual-path following method and the projected gradient algorithm.

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M3 - Article

SN - 1446-1811

VL - 52

SP - C949-C966

JO - ANZIAM Journal

JF - ANZIAM Journal

ER -

Solving variational inequalities using wavelet methods

Abstract

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