代码搜索:Approximation

找到约 1,542 项符合「Approximation」的源代码

代码结果 1,542
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m nonlin_taylor.m

function b = nonlin_taylor(a, nonlin) % TANH Hyperbolic tangent of a propability distribution % % The result is calculated using second order Taylor approximation % for expectation and first order for
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nb pcgm.nb

(* CONJUGATE GRADIENT ALGORITHM 7.5 * * To solve Ax = b given the preconditioning matrix C inverse * and an initial approximation x(0) * * Input: the number of equations and unknowns n;
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m alg101.m

% NEWTON'S METHOD FOR SYSTEMS ALGORITHM 10.1 % % To approximate the solution of the nonlinear system F(X)=0 given % an initial approximation X: % % INPUT: Number n of equations and unknowns; in
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m alg101.m

% NEWTON'S METHOD FOR SYSTEMS ALGORITHM 10.1 % % To approximate the solution of the nonlinear system F(X)=0 given % an initial approximation X: % % INPUT: Number n of equations and unknowns; in
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m heightamb.m

function ha = heightamb(bperp) % HEIGHTAMB -- Approximation of height ambiguity for perpendicular baseline. % HA = HEIGHTAMB(BPERP) returns height ambiguities of matrix BPERP. % Fixed parameters:
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m heightamb.m

function ha = heightamb(bperp) % HEIGHTAMB -- Approximation of height ambiguity for perpendicular baseline. % HA = HEIGHTAMB(BPERP) returns height ambiguities of matrix BPERP. % Fixed parameters:
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txt alg101.txt

> restart; > # NEWTON'S METHOD FOR SYSTEMS ALGORITHM 10.1 > # > # To approximate the solution of the nonlinear system F(X)=0 given > # an initial approximation X: > # > # INPUT: Number n of eq
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txt alg072.txt

> restart; > # GAUSS-SEIDEL ITERATIVE TECHNIQUE ALGORITHM 7.2 > # > # To solve Ax = b given an initial approximation x(0). > # > # INPUT: the number of equations and unknowns n; the entries >
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txt alg101.txt

> restart; > # NEWTON'S METHOD FOR SYSTEMS ALGORITHM 10.1 > # > # To approximate the solution of the nonlinear system F(X)=0 given > # an initial approximation X: > # > # INPUT: Number n of eq
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txt alg072.txt

> restart; > # GAUSS-SEIDEL ITERATIVE TECHNIQUE ALGORITHM 7.2 > # > # To solve Ax = b given an initial approximation x(0). > # > # INPUT: the number of equations and unknowns n; the entries >