{"product_id":"algorithms-for-minimization-without-derivatives-dover-books-on-mathematics","title":"Algorithms for Minimization Without Derivatives (Dover Books on Mathematics)","description":"\n\u003ctable align=\"center\" border=\"0\" cellpadding=\"2\" cellspacing=\"0\" width=\"100%\"\u003e\n\u003ctr\u003e\n\u003ctd class=\"productDetailSmallElements\"\u003e\n\u003cp\u003e\n\u003cstrong\u003eMarc Notes\u003c\/strong\u003e:\u003cbr\u003e\n\t\t\t\t\t\t\t\tIncludes bibliographical references and index.;This text for graduate students and researchers proposes improvements to existing algorithms, extends their related mathematical theories, and offers details on new algorithms for approximating local and global minima.\u003cbr\u003e\u003cbr\u003e\n\u003cstrong\u003eTable of Contents\u003c\/strong\u003e:\u003cbr\u003e\n\t\t\t\t\t\t\t\tPREFACE TO DOVER EDITION \n\u003cbr\u003e PREFACE \n\u003cbr\u003e1 INTRODUCTION AND SUMMARY \n\u003cbr\u003e 1.1 Introduction \n\u003cbr\u003e 1.2 Summary \n\u003cbr\u003e2 SOME USEFUL RESULTS ON TAYLOR SERIES, DIVIDED DIFFERENCIES, AND LAGRANGE INTERPOLATION \n\u003cbr\u003e 2.1 Introduction \n\u003cbr\u003e 2.2 Notation and definitions \n\u003cbr\u003e 2.3 Truncated Taylor series \n\u003cbr\u003e 2.4 Lagrange interpolation \n\u003cbr\u003e 2.5 Divided differences \n\u003cbr\u003e 2.6 Differentiating the error \n\u003cbr\u003e3 THE USE OF SUCCESSIVE INTERPOLATION FOR FINDING SIMPLE ZEROS OF A FUNCTION AND ITS DERIVATIVES \n\u003cbr\u003e 3.1 Introduction \n\u003cbr\u003e 3.2 The definition of order \n\u003cbr\u003e 3.3 Convergence to a zero \n\u003cbr\u003e 3.4 Superlinear convergence \n\u003cbr\u003e 3.5 Strict superlinear convergence \n\u003cbr\u003e 3.6 The exact order of convergence \n\u003cbr\u003e 3.7 Stronger results for q = 1 and 2 \n\u003cbr\u003e 3.8 Accelerating convergence \n\u003cbr\u003e 3.9 Some numerical examples \n\u003cbr\u003e 3.10 Summary \n\u003cbr\u003e4 AN ALGORITHM WITH GUARANTEED CONVERGENCE FOR FINDING A ZERO OF A FUNCTION \n\u003cbr\u003e 4.1 Introduction \n\u003cbr\u003e 4.2 The algorithm \n\u003cbr\u003e 4.3 Convergence properties \n\u003cbr\u003e 4.4 Practical tests \n\u003cbr\u003e 4.5 Conclusion \n\u003cbr\u003e 4.6 ALGOL 60 procedures \n\u003cbr\u003e5 AN ALGORITHM WITH GUARANTEED CONVERGENCE FOR FINDING A MINIMUM OF A FUNCTION OF ONE VARIABLE \n\u003cbr\u003e 5.1 Introduction \n\u003cbr\u003e 5.2 Fundamental limitations because of rounding errors \n\u003cbr\u003e 5.3 Unimodality and d-unimodality \n\u003cbr\u003e 5.4 An algorithm analogous to Dekker's algorithm \n\u003cbr\u003e6 GLOBAL MINIMIZATION GIVEN AN UPPER BOUND ON THE SECOND DERIVATIVE \n\u003cbr\u003e 6.1 Introduction \n\u003cbr\u003e 6.2 The basic theorems \n\u003cbr\u003e 6.3 An algorithm for global minimization \n\u003cbr\u003e 6.4 The rate of convergence in some special cases \n\u003cbr\u003e 6.5 A lower bound on the number of function evaluations required \n\u003cbr\u003e 6.6 Practical tests \n\u003cbr\u003e 6.7 Some extensions and generalizations \n\u003cbr\u003e 6.8 An algorithm for global minimization of a function of several variables \n\u003cbr\u003e 6.9 Summary and conclusions \n\u003cbr\u003e 6.10 ALGOL 60 procedures \n\u003cbr\u003e7 A NEW ALGORITHM FOR MINIMIZING A FUNCTION OF SEVERAL VARIABLES WITHOUT CALCULATING DERIVATIVES \n\u003cbr\u003e 7.1 Introduction and survey of the literature \n\u003cbr\u003e 7.2 The effect of rounding errors \n\u003cbr\u003e 7.3 Powell's algorithm \n\u003cbr\u003e 7.4 The main modification \n\u003cbr\u003e 7.5 The resolution ridge problem \n\u003cbr\u003e 7.6 Some further details \n\u003cbr\u003e 7.7 Numerical results and comparison with other methods \n\u003cbr\u003e 7.8 Conclusion \n\u003cbr\u003e 7.9 An ALGOL W procedure and test program \n\u003cbr\u003e BIBLIOGRAPHY \n\u003cbr\u003e APPENDIX: FORTRAN subroutines \n\u003cbr\u003e INDEX \n\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\n\u003cstrong\u003ePublisher Marketing\u003c\/strong\u003e:\u003cbr\u003e\n\t\t\t\t\t\t\t\tOutstanding text for graduate students and researchers proposes improvements to existing algorithms, extends their related mathematical theories, and offers details on new algorithms for approximating local and global minima. 1973 edition.\u003cbr\u003e\u003cbr\u003e\n\u003c\/p\u003e\n\u003cbr\u003e\n\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\n","brand":"Dover Publications","offers":[{"title":"Default Title","offer_id":46581099331715,"sku":"SPTM-9780486419985","price":14.95,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0564\/6830\/8099\/files\/9780486419985_spiral_60c86db2-cd51-41b2-ba0d-2dfe5417b042.png?v=1770801817","url":"https:\/\/sebink.com\/products\/algorithms-for-minimization-without-derivatives-dover-books-on-mathematics","provider":"Sebink","version":"1.0","type":"link"}