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| Titel: |
Numerical algorithms for solving nonlinear l -norm estimation problems: Part i - a first-order gradient algorithm for well-conditioned small residual problems |
| Auteur: |
Gonin, R. |
| Verschenen in: |
Communications in statistics |
| Paginering: | Jaargang 15 (1986) nr. 3 pagina's 801-813 |
| Jaar: |
1986 |
| Inhoud: |
In this paper an algorithm for solving nonlinear LP: -norm estimation problems is derived. It uses the structure of the LP: -norm problem and is an extension of the classical Gauss-Newton method designed to solve nonlinear least squares problems. It is shown that the Gauss-Newton method is imbedded within this new algorithm and hence only first-order partial derivatives need be considered. The use of second-order derivative information, which is costly from a computational point of view, is ignored. Expressions for the first- and second-order partial derivatives will be obtained using a compact matrix notation. The algorithm is efficient in solving fairly well-behaved, small, residual nonlinear LP: -norm estimation problems when 1 > p > ∞. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 13 van 23 gevonden artikelen
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