## Abstract A sequence of leastβsquares problems of the form min~__y__~β₯__G__^1/2^(__A__^T^ __y__β__h__)β₯~2~, where __G__ is an __n__Γ__n__ positiveβdefinite diagonal weight matrix, and __A__ an __m__Γ__n__ (__m__β©½__n__) sparse matrix with some dense columns; has many applications in linear program
Asynchronous distributed solution of large scale nonlinear inversion problems
β Scribed by V. Pereyra
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 93 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0168-9274
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β¦ Synopsis
In this paper we consider large scale nonlinear least squares problems whose objective functions are very expensive to evaluate, and whose Jacobian matrices are generally ill-conditioned and have an almost block diagonal structure. We prove the convergence of an asynchronous iteration to solve this kind of problems under standard assumptions. The method is naturally parallelizable and thus is applicable to practical inversion problems, as those arising in seismic exploration for hydrocarbons.
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