Local and Superlinear Convergence for Truncated Projections Methods

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dc.contributor.authorSteihaug, Trond
dc.date.accessioned2018-06-18T17:18:54Z
dc.date.available2018-06-18T17:18:54Z
dc.date.issued1981-10
dc.date.noteOctober 1981
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.
dc.format.extent28 pp
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>.
dc.identifier.digitalTR81-02
dc.identifier.urihttps://hdl.handle.net/1911/101544
dc.language.isoeng
dc.titleLocal and Superlinear Convergence for Truncated Projections Methods
dc.typeTechnical report
dc.type.dcmiText
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