Local and Superlinear Convergence for Truncated Projections Methods

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dc.contributor.authorSteihaug, Tronden_US
dc.date.accessioned2018-06-18T17:18:54Zen_US
dc.date.available2018-06-18T17:18:54Zen_US
dc.date.issued1981-10en_US
dc.date.noteOctober 1981en_US
dc.description.abstractLeast change secant updates can be obtained as the limit of iterated projections based on other secant updates. We show that these iterated projections can be terminated or truncated after any positive number of iterations and the local and the superlinear rate of convergence are still maintained. The truncated iterated projections method is used to find sparse and symmetric updates that are locally and superlinearly convergent.en_US
dc.format.extent28 ppen_US
dc.identifier.citationSteihaug, Trond. "Local and Superlinear Convergence for Truncated Projections Methods." (1981) <a href="https://hdl.handle.net/1911/101544">https://hdl.handle.net/1911/101544</a>.en_US
dc.identifier.digitalTR81-02en_US
dc.identifier.urihttps://hdl.handle.net/1911/101544en_US
dc.language.isoengen_US
dc.titleLocal and Superlinear Convergence for Truncated Projections Methodsen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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