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Factorization of Boundary Value Problems Using the Invariant Embedding Method
Factorization of Boundary Value Problems Using the Invariant Embedding Method
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244,85 €
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Factorization Method for Boundary Value Problems by Invariant Embedding presents a new theory for linear elliptic boundary value problems. The authors provide a transformation of the problem in two initial value problems that are uncoupled, enabling you to solve these successively. This method appears similar to the Gauss block factorization of the matrix, obtained in finite dimension after discretization of the problem. This proposed method is comparable to the computation of optimal feedbacks…
  • Leidėjas:
  • Metai: 2016
  • Puslapiai: 200
  • ISBN-10: 1785481436
  • ISBN-13: 9781785481437
  • Formatas: 15 x 23.1 x 1.8 cm, kieti viršeliai
  • Kalba: Anglų

Factorization of Boundary Value Problems Using the Invariant Embedding Method (el. knyga) (skaityta knyga) | knygos.lt

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Factorization Method for Boundary Value Problems by Invariant Embedding presents a new theory for linear elliptic boundary value problems. The authors provide a transformation of the problem in two initial value problems that are uncoupled, enabling you to solve these successively. This method appears similar to the Gauss block factorization of the matrix, obtained in finite dimension after discretization of the problem. This proposed method is comparable to the computation of optimal feedbacks for linear quadratic control problems.

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  • Autorius: Jacques Henry
  • Leidėjas:
  • Metai: 2016
  • Puslapiai: 200
  • ISBN-10: 1785481436
  • ISBN-13: 9781785481437
  • Formatas: 15 x 23.1 x 1.8 cm, kieti viršeliai
  • Kalba: Anglų

Factorization Method for Boundary Value Problems by Invariant Embedding presents a new theory for linear elliptic boundary value problems. The authors provide a transformation of the problem in two initial value problems that are uncoupled, enabling you to solve these successively. This method appears similar to the Gauss block factorization of the matrix, obtained in finite dimension after discretization of the problem. This proposed method is comparable to the computation of optimal feedbacks for linear quadratic control problems.

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