{"product_id":"9781771886222","title":"Computation of Generalized Matrix Inverses and Applications","description":"\u003ch1\u003eComputation of Generalized Matrix Inverses and Applications\u003c\/h1\u003e\u003ch3\u003eIvan Stanimirović\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMathematics \/ General\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003eThis volume offers a gradual exposition to matrix theory as a subject of linear algebra. It presents both the theoretical results in generalized matrix inverses and the applications. The book is as self-contained as possible, assuming no prior knowledge of matrix theory and linear algebra.\u003c\/p\u003e\n\u003cp\u003eThe book first addresses the basic definitions and concepts of an arbitrary generalized matrix inverse with special reference to the calculation of \u003ci\u003e{i,j,...,k}\u003c\/i\u003e inverse and the Moore–Penrose inverse. Then, the results of LDL* decomposition of the full rank polynomial matrix are introduced, along with numerical examples. Methods for calculating the Moore–Penrose’s inverse of rational matrix are presented, which are based on LDL* and QDR decompositions of the matrix. A method for calculating the \u003ci\u003eA(2)T;S\u003c\/i\u003e inverse using LDL* decomposition using methods is derived as well as the symbolic calculation of \u003ci\u003eA(2)T;S\u003c\/i\u003e inverses using QDR factorization.\u003c\/p\u003e\n\u003cp\u003eThe text then offers several ways on how the introduced theoretical concepts can be applied in restoring blurred images and linear regression methods, along with the well-known application in linear systems. The book also explains how the computation of generalized inverses of matrices with constant values is performed. It covers several methods, such as methods based on full-rank factorization, Leverrier–Faddeev method, method of Zhukovski, and variations of the partitioning method.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\u003cp\u003e\u003cstrong\u003eIvan Stanimirović, PhD\u003c\/strong\u003e, is currently with the Department of Computer Science, Faculty of Sciences and Mathematics at the University of Niš, Serbia, where he is an Assistant Professor. He formerly was with the Faculty of Management at Megatrend University, Belgrade, as a Lecturer. His work spans from multi-objective optimization methods to applications of generalized matrix inverses in areas such as image processing and restoration and computer graphics. His current research interests include computing generalized matrix inverses and its applications, applied multi-objective optimization and decision making, as well as deep learning neural networks. Dr. Stanimirović was the Chairman of a workshop held at 13th Serbian Mathematical Congress, Vrnjačka banja, Serbia, in 2014.\u003c\/p\u003e\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e13 December 2017\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eCRC Press\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eApple Academic Press\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9781771886222\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e280\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e24.75\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"CRC Press","offers":[{"title":"Default Title","offer_id":63547465007244,"sku":"9781771886222","price":139.5,"currency_code":"USD","in_stock":true}],"url":"https:\/\/lateknightbooks.com\/products\/9781771886222","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}