{"product_id":"the-theory-of-matrices-in-numerical-analysis-paperback","title":"The Theory of Matrices in Numerical Analysis - Paperback","description":"\u003cp\u003eby \u003cb\u003eAlston S. Householder\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eThis text explores aspects of matrix theory that are most useful in developing and appraising computational methods for solving systems of linear equations and for finding characteristic roots. Suitable for advanced undergraduates and graduate students, it assumes an understanding of the general principles of matrix algebra, including the Cayley-Hamilton theorem, characteristic roots and vectors, and linear dependence.\u003cbr\u003eAn introductory chapter covers the Lanczos algorithm, orthogonal polynomials, and determinantal identities. Succeeding chapters examine norms, bounds, and convergence; localization theorems and other inequalities; and methods of solving systems of linear equations. The final chapters illustrate the mathematical principles underlying linear equations and their interrelationships. Topics include methods of successive approximation, direct methods of inversion, normalization and reduction of the matrix, and proper values and vectors. Each chapter concludes with a helpful set of references and problems.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 270\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.61 x 8.16 x 5.38 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e January 20, 2006\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":47453400563890,"sku":"9780486449722","price":16.15,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0770\/3891\/1666\/files\/8d3847b95df4652ec3552528ce4e6e73.webp?v=1778829699","url":"https:\/\/box.dadyminds.org\/products\/the-theory-of-matrices-in-numerical-analysis-paperback","provider":"DADYMINDS BOX","version":"1.0","type":"link"}