Separating periodic signals from their aperiodic background

"Sines and Splines - Variable Projection" demonstrates the separation of a signal into its periodic and aperiodic portions, whereby the period of the periodic portion is unknown. Therfore the signal

Computes the B-spline approximation from a set of coordinates. Supports periodicity and n-th order approximation.

Computes the B-spline approximation from a set of coordinates (knots).The number of points per interval (default: 10) and the order of the B-spline (default: 3) can be changed. Periodic boundaries

Implements a model for Cubic Smoothing Splines with periodic boundary conditions

Smoothing cubic splines are implemented with periodic conditions, so that closed curves in any dimension can be approximated. It includes a test function to demonstrate it.Theoretical arguments

Fit a spline to noisy data

controlled by the selection of breaks. SPLINEFIT:- A curve fitting tool based on B-splines- Splines on ppform (piecewise polynomial)- Any spline order (cubic splines by default)- Periodic boundary conditions

PERIODICAL PIECEWISE CUBIC HERMITE INTERPOLATING POLYNOMIAL: THE FUNCTIONS PERPCHIP AND PERSPLINE

The functions pchip and spline of matlab are adapted to the periodical case: perpchip and perspline. Some examples are given

Define 2D geometry, ICEM CFD 2D surface blocking mesh, and Fluent journals in Matlab

Define points, lines/splines, surfaces, and mesh parameters in Matlab and create ICEM replay files to generate, define, and export a 2D surface blocking mesh to Ansys Fluent. The toolbox handles

Compute spline function and its derivative

Some set of tools that allows to interpolate on grid a spline function and compute its derivative.Multi-dimensional supported (but rather slow)Natural / Not-a-knot / periodic conditionsIt is still a

Z = SMOOTH1Q(Y) smoothes data Y using a DCT- or FFT-based spline smoothing method

Z = SMOOTH1Q(Y,S) smoothes the data Y using a DCT- or FFT-based spline smoothing method. Non finite data (NaN or Inf) are treated as missing values. S is the smoothing parameter. It must be a real

Distance based interpolation along a general curve in space

is to be a spline, perhaps interpolated as a function of chordal arclength between the points, this gets a bit more difficult. A nice trick is to formulate the problem in terms of differential

Supersampling function using Optimal Maximal-Order-Minimal-Support as kernel.

processing, which is why sinc (the kernel that gives ideal reconstruction) is not used in practice. B-spline based interpolating kernels are usually used in spline interpolation. MOMS functions are constructed

Here there are several kinds of Mathematical problems!

n = 3 , H_0ibld020105.m Hermite polynomials for n = 3, H_1ibld020106.m Bezier curve for Bezier polynomials of degree n = 3bld020107.m Spline curvebld020201.m Legendre polynomialsbld020202.m Chebyshev