11 results

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

SPLINEFIT

version 1.0.0

by Jonas Lundgren

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

Spline derivative

version 1.0.0.0

by Bruno Luong

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

interparc

version 1.3.0.0

by John D'Errico

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