Matlab/Octave Compatibility toolbox
- Matlab/Octave Compatibility toolbox
- moc_angle — Compute atan(imag(A),real(A)) in radians
- moc_cholinv — Use the Cholesky factorization to compute the inverse of the symmetric positive definite matrix a.
- moc_circshift — Circularly shift the values of the array x
- moc_columns — gives the number of columns from A
- moc_conv — Convolve two vectors.
- moc_conv2 — performs 2D convolution of matrices a and b
- moc_corr — Compute matrix of correlation coefficients.
- moc_corrcov — Compute correlation matrix from covariance matrix.
- moc_cov — Compute the covariance matrix.
- moc_deal — Copy the input parameters into the corresponding output parameters.
- moc_fft — matlab compatible fft
- moc_fliplr — Return a copy of X with the order of the columns reversed.
- moc_flipud — Return a copy of X with the order of the rows reversed.
- moc_fzero — solves the scalar nonlinear equation such that F(X) == 0
- moc_gaussian — Generate an n-point gaussian convolution window
- moc_ifft — matlab compatible ifft
- moc_inpolygon — determines if points are inside or outside of a given polygon
- moc_islogical — checks if A is boolean
- moc_ismember — Checks which elements of one matrix are member of an other matrix
- moc_null — Return an orthonormal basis of the null space of A.
- moc_poly — poly function from octave
- moc_polyfit — Return the coefficients of a polynomial
- moc_polyval — Evaluate the polynomial p at the specified values of x
- moc_postpad — append the scalar
- moc_prepad — prepend the scalar
- moc_randi — Return random integers in a given range
- moc_range — Range of values
- moc_rot90 — rotates the given matrix clockwise by 90 degrees.
- moc_rows — gives the number of rows from A
- moc_size_equal — checks if A and B have the same size
- moc_spdiags — A generalization of the function 'diag'
- moc_squeeze — Remove singleton dimensions from X and return the result
- moc_sumsq — calculates the sum of squares.
- moc_unique — Return the unique elements of x, sorted in ascending order.
- moc_unwrap — Unwrap radian phases by adding multiples of 2*pi
- moc_xcorr — Compute correlation R_xy of X and Y for various lags k:
- moc_xcorr2 — Compute the 2D correlation
- moc_xcov — Compute covariance at various lags[=correlation(x-mean(x),y-mean(y))].