Description

Book Synopsis
1 Regularizing Algorithms for Linear Ill-Posed Problems: Unified Approach.- 2 Iteration Steepest Descent Methods for Linear Operator Equations.- 3 Iteration Conjugate Direction Methods for Linear Operator Equations.- 4 Iteration Steepest Descent Methods for Nonlinear Operator Equations.- 5 Iteration Methods for Ill-Posed Constrained Minimization Problems.- 6 Descriptive Regularization Algorithms on the Basis of the Conjugate Gradient Projection Method.

Trade Review
`The book will be useful for specialists who in their theoretical and applied investigations deal with ill-posed and inverse problems.'
Mathematical Reviews Clippings (2001)


Table of Contents
Preface. Introduction. 1. Regularizing Algorithms for Linear Ill-Posed Problems: Unified Approach. 2. Iteration Steepest Descent Methods for Linear Operator Equations. 3. Iteration Conjugate Direction Methods For Linear Operator Equations. 4. Iteration Steepest Descent Methods for Nonlinear Operator Equations. 5. Iteration Methods for Ill-Posed Constrained Minimization Problems. 6. Descriptive Regularization Algorithms on the Basis of the Conjugate Gradient Projection Method. Bibliography. Index.

Regularization of IllPosed Problems by Iteration Methods 499 Mathematics and Its Applications

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    A Hardback by S.F. Gilyazov, N.L. Gol'dman

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      Book details

      Publisher Springer
      Published 12/31/1999 12:00:00 AM
      ISBN-13 9780792361312
      978-0792361312
      ISBN-10 0792361318
      Also in:
      Mathematics Differential calculus and equations Functional analysis and transforms Technology, Engineering & Agriculture Automotive technology and trades

      Description

      Book Synopsis
      1 Regularizing Algorithms for Linear Ill-Posed Problems: Unified Approach.- 2 Iteration Steepest Descent Methods for Linear Operator Equations.- 3 Iteration Conjugate Direction Methods for Linear Operator Equations.- 4 Iteration Steepest Descent Methods for Nonlinear Operator Equations.- 5 Iteration Methods for Ill-Posed Constrained Minimization Problems.- 6 Descriptive Regularization Algorithms on the Basis of the Conjugate Gradient Projection Method.

      Trade Review
      `The book will be useful for specialists who in their theoretical and applied investigations deal with ill-posed and inverse problems.'
      Mathematical Reviews Clippings (2001)


      Table of Contents
      Preface. Introduction. 1. Regularizing Algorithms for Linear Ill-Posed Problems: Unified Approach. 2. Iteration Steepest Descent Methods for Linear Operator Equations. 3. Iteration Conjugate Direction Methods For Linear Operator Equations. 4. Iteration Steepest Descent Methods for Nonlinear Operator Equations. 5. Iteration Methods for Ill-Posed Constrained Minimization Problems. 6. Descriptive Regularization Algorithms on the Basis of the Conjugate Gradient Projection Method. Bibliography. Index.

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