![]() There are two significant limitations on Fourier interpolation. Interpft assumes that the interpolated function is periodic, and soĪssumptions are made about the endpoints of the interpolation. If dim is specified, then interpolate along the dimension dim. N-dimensional array, the interpolation is performed on each column of Theĭata in x is assumed to be equispaced. If x is a vector then x is resampled with n points. ![]() : interpft ( x, n) : interpft ( x, n, dim) Interpolation methods for a step functionįourier interpolation, is a resampling technique where a signal isĬonverted to the frequency domain, padded with zeros and then "linear" methods in all other cases, the x-values must beįigure 29.2: Comparison of the second derivative of the "pchip" and "spline" Or right-continuous interpolant, respectively.ĭiscontinuous interpolation is only allowed for "nearest" and The options "left" or "right" to select a left-continuous The continuity condition of the interpolant may be specified by using If x is decreasing, the default discontinuous ![]() If x is increasing, the default discontinuous interpolant is May be at most 2 consecutive points with the same value. There is an equivalence, such that ppval (interp1 ( x,ĭuplicate points in x specify a discontinuous interpolant. Object can later be used with ppval to evaluate the interpolation. If the string argument "pp" is specified, then xi should notīe supplied and interp1 returns a piecewise polynomial object. Number, then replace values beyond the endpoints with that number. If extrap is the string "extrap", then extrapolate valuesīeyond the endpoints using the current method. This is usually faster,Īnd is never slower. To assume that x is uniformly spaced, and only x(1)Īnd x(2) are referenced. Interpolation with smooth first derivative.Ĭubic spline interpolation-smooth first and second derivativesĪdding ’*’ to the start of any method above forces interp1 Piecewise cubic Hermite interpolating polynomial-shape-preserving Linear interpolation from nearest neighbors. If y is a matrix or an N-dimensionalĪrray, the interpolation is performed on each column of y. If not specified, x is taken to be the indices of y Interpolate input data to determine the value of yi at the points : yi = interp1 ( x, y, xi) : yi = interp1 ( y, xi) : yi = interp1 (…, method) : yi = interp1 (…, extrap) : yi = interp1 (…, "left") : yi = interp1 (…, "right") : pp = interp1 (…, "pp") Polynomial InterpolationĪnd Interpolation on Scattered Data describe additional methods. ![]() Octave supports several methods for one-dimensional interpolation, most Next: Multi-dimensional Interpolation, Up: Interpolation Y = sin(2*pi*f*t) % Test signal sampled accurately In addition to providing a better value for the distinct peak frequency in the spectrum (compare plots 1 & 3), the interpolation method also results in a lower mean squared error. It supposes a 5 Hz sine wave test signal, with a nominal sample rate of 16 Hz but with jitter added to the sample times. I have found, to my surprise, that interpolating the data by using the Matlab function interp1() gives more accurate results than resampling by using the Matlab function resample().īelow is a simple illustration. Without changing sample rates, I need to resample the data uniformly. I have a task that requires that I deal with nonuniformly sampled signals (not plain vanilla time series data).
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