5 edition of **Approximate linear algebraic equations** found in the catalog.

- 153 Want to read
- 15 Currently reading

Published
**1971**
by Van Nostrand Reinhold in London, New York
.

Written in English

- Equations.,
- Approximation theory.

**Edition Notes**

Includes bibliographies and index.

Statement | [by] I. B. Kuperman. |

Series | The New university mathematics series |

Classifications | |
---|---|

LC Classifications | QA214 .K86 |

The Physical Object | |

Pagination | xii, 225 p. |

Number of Pages | 225 |

ID Numbers | |

Open Library | OL5706323M |

ISBN 10 | 0442045468 |

LC Control Number | 70160200 |

Approximate solution see Least-squares. Augmented matrix see Matrix. Basis. algebraic multiplicity of see Algebraic multiplicity. inconsistent see System of linear equations, inconsistent. solving Important Note. Volume. and length Example. of a parallelepiped Theorem. of a region Theorem. In the field of numerical analysis, numerical linear algebra is an area to study methods to solve problems in linear algebra by numerical following problems will be considered in this area: Numerically solving a system of linear equations.; Numerically solving an eigenvalue problem for a given matrix.; Computing approximate values of a matrix-valued function.

vector spaces, linear maps, determinants, and eigenvalues and eigenvectors. Another standard is book’s audience: sophomores or juniors, usually with a background of at least one semester of calculus. () Numerical solution of large-scale Lyapunov equations, Riccati equations, and linear-quadratic optimal control problems. Numerical Linear Algebra with Applications , () Numerical solutions of matrix differential models using cubic matrix splines by:

How to Make Linear Approximations Because ordinary functions are locally linear (that means straight) — and the further you zoom in on them, the straighter they look—a line tangent to a function is a good approximation of the function near the point of tangency. Approximation by Algebraic Numbers. Separation of variables for partial differential equations; an eigenfunction approach. Stochastic Partial Differential Equations and Applications: VII. Approximations and endomorphism algebras of modules. Statistical multisource-multitarget information fusion. Vibration of continuous systems.

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Additional Physical Format: Online version: Kuperman, Israel B. Approximate linear algebraic equations. London, New York, Van Nostrand Reinhold, Linear equations can vary from a set of two to a set having or more equations. In most cases, we can employ Cramer's rule to solve a set of two or three linear algebraic equations.

However, for systems of many linear equations, the algebraic computation becomes too. The fundamental idea of Newton’s method is to approximate the original function \(f(x)\) by a straight line, i.e., a linear function, since it is straightforward to solve linear equations.

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Linear Integral Equations: Theory and Technique is an chapter text that covers the theoretical and methodological aspects of linear integral equations. After a brief overview of the fundamentals of the equations, this book goes on dealing with specific integral equations with separable kernels and a method of successive approximations.

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˜c is the constant vector of the system of equations and A is the matrix of the system's coefficients. We can write the solution to these equations as x 1c r-r =A, () thereby reducing the solution of any algebraic system of linear equations to finding the inverse of the coefficient Size: KB.

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Author(s): Simon J.A. Malham. This self-contained introduction to numerical linear algebra provides a comprehensive, yet concise, overview of the subject. It includes standard material such as direct methods for solving linear systems and least-squares problems, error, stability and conditioning, basic iterative methods and the calculation of Cited by: 3.

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In mathematics, an algebraic equation or polynomial equation is an equation of the form = where P is a polynomial with coefficients in some field, often the field of the rational most authors, an algebraic equation is univariate, which means that it involves only one the other hand, a polynomial equation may involve several variables, in which case it is called.

SECTION ITERATIVE METHODS FOR SOLVING LINEAR SYSTEMS Theorem Convergence of the Jacobi and Gauss-Seidel Methods If A is strictly diagonally dominant, then the system of linear equations given by has a unique solution to which the Jacobi method and the Gauss-Seidel method will con-verge for any initial approximation.

Ax bFile Size: KB.As Anon mentions, linear least squares is the standard method for solving this problem. It involves solving the system of linear equations.

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