Dynamic programming and mean square deviation.
Purchase Print Copy
|Add to Cart||Paperback12 pages||$15.00||$12.00 20% Web Discount|
An application of the functional equation technique of dynamic programming to the treatment of some quadratic variational problems and linear equations. The author attempts (1) to determine the minimum value of the quadratic deviation <>, where f(x) is a given function of <>, a given sequence of real functions; (2) to minimize the quadratic form <> over all real <> , where <> and <> are given real sequences; and (3) to discuss the problem of solving the linear system Ax = b, under the assumption that A is positive definite.
This report is part of the RAND Corporation Paper series. The paper was a product of the RAND Corporation from 1948 to 2003 that captured speeches, memorials, and derivative research, usually prepared on authors' own time and meant to be the scholarly or scientific contribution of individual authors to their professional fields. Papers were less formal than reports and did not require rigorous peer review.
This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.
The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.