Matlab Database > Author List > Files of Alain kapitho

Files

  • 13 files found, created by author "Alain kapitho".

  • Programs

    Title Summary Primary Author Date
    Composite trapezoidal rule
    Function trapz(a, b, n) approximates the integral of f(x) in the interval [a; b] using the trapezoidal composite rule. n is the number of subintervals. Alain kapitho 2006-01-20
    Fixed-point for functions of several variables
    The solution to a system of nonlinear equations may be found with fixed_point_systems(x0, N). As in the case of a single nonlinear equation, the system compactly written as F(x) = 0, has to be rewritten in the sub-function as x = G(x). The output consists Alain kapitho 2006-01-11
    Fixed-Point iteration
    Function fixed_point(p0, N) attempts to find the solution of an equaion f(x) = 0, that the user has to rewrite in the fixed-point form x = g(x). The iterative scheme is then x(k+1) = g(x(k)) and implemented N times, starting with an initial approximation Alain kapitho 2006-01-11
    Gauss-Jordan with multilple right-hand side vectors
    The function allows to solve simultaneoulsy different linear systems with the same coefficient matrix A using the Gauss-Jordan algorithm Alain kapitho 2005-11-15
    Gauss-Seidel iterative method
    Function Gauss_Seidel(A, b, N) iteratively solves a system of linear equations whereby A is the coefficient matrix, b the right-hand side column vector and N the maximum number of iterations. A transition/iteration matrix approach is implemented, with Tg Alain kapitho 2007-08-14
    Gaussian elimination with partial pivoting
    Solving a n-by-n linear system of equations using Gaussian elimination with partial pivoting Alain kapitho 2005-11-18
    Jacobi iterative method
    Function Jacobi(A, b, N) iteratively solves a system of linear equations whereby A is the coefficient matrix, b the right-hand side column vector and N the maximum number of iterations. As with the Gauss_Seidel(A, b, N) function, a transition matrix appro Alain kapitho 2007-08-14
    Least-squares polynomial approximations
    Given n points in x-y coordinates, function Least_Squares(x, y, m) constructs the least-squares polynomial of degree m. The call to the function returns a vector c whose components c0, c1, ..., cm are the coefficients of the polynomial. Alain kapitho 2006-01-11
    Newton interpolation polynomial with divided differences
    given n points in x-y coordinates, function divided_diff(x,y,x0) constructs the Newton's interpolatory polynomial of degree n-1 and evaluates it at the specified point x0. Alain kapitho 2006-01-11
    Runge-Kutta 4 for systems of ODE
    Function rk4_systems(a, b, N, alpha) approximates the solution of a system of differential equations, by the method of Runge-kutta order 4. a and b are the endpoints of the interval, N the number of subdivisions, and alpha the initial conditions Alain kapitho 2006-01-20
    Runge-Kutta method of order 4
    Given an initial-value problem of the form y' = f(t,y), function runge_kutta4(a, b, N, alpha) approximates its solution in the interval [a; b] using the Runge-Kutta method of order 4. Alain kapitho 2006-01-11
    Simpson composite integration
    Function simps(a, b, n) approximates the integral of f(x) using the composite Simpson rule. The user needs to specify f(x) as a sub-function at the bottom of the file Alain kapitho 2006-01-20
    Successive Over-relaxation Solver
    Function SOR(A,b,N) solves iteratively the linear system Ax = b, N being the maximum number of iterations. Iterations are implemented in matrix form as x(k+1) = Tw*x(k) + c, with Tw being the transition/iteration matrix and c a constant vector. the optim Alain kapitho 2007-08-14