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Interpolation — increase sampling rate by integer factor


y = interp(x,r)
y = interp(x,r,n,alpha)
[y,b] = interp(x,r,n,alpha)


Interpolation increases the original sampling rate of a sequence to a higher rate. It is the opposite of decimation. interp inserts 0s into the original signal and then applies a lowpass interpolating filter to the expanded sequence.


y = interp(x,r) increases the sampling rate of x, the input signal, by a factor of r. The interpolated vector, y, is r times as long as the original input, x.

y = interp(x,r,n,alpha) specifies two additional values. n is half the number of original sample values used to interpolate the expanded signal. Its default value is 4. It should ideally be less than or equal to 10. alpha is the normalized cutoff frequency of the input signal, specified as a fraction of the Nyquist frequency. It defaults to 0.5. The lowpass interpolation filter has length 2*n*r + 1.

[y,b] = interp(x,r,n,alpha) also returns a vector, b, with the filter coefficients used for the interpolation.

Input Arguments

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Input signal, specified as a vector.

Data Types: double

Interpolation factor, specified as a positive integer scalar.

Data Types: double

Half-number of input samples used for interpolation, specified as a positive integer scalar. n should never be greater than 10.

Data Types: double

Normalized cutoff frequency of the input signal, specified as a positive real scalar not greater than 1. A value of 1 means that the signal occupies the full Nyquist interval.

Data Types: double

Output Arguments

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Interpolated signal, returned as a vector.

Data Types: double

Lowpass interpolation filter coefficients, returned as a column vector.

Data Types: double


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Create a sinusoidal signal sampled at 1 kHz. Interpolate it by a factor of four.

t = 0:0.001:1;
x = sin(2*pi*30*t) + sin(2*pi*60*t);
y = interp(x,4);

Plot the original and interpolated signals.

subplot 211
grid on
xlabel 'Sample number',ylabel Original
subplot 212
grid on
xlabel 'Sample number',ylabel Interpolated


interp uses the lowpass interpolation algorithm 8.1 described in [1].

  1. It expands the input vector to the correct length by inserting 0s between the original data values.

  2. It designs a special symmetric FIR filter that allows the original data to pass through unchanged and interpolates to minimize the mean-square error between the interpolated points and their ideal values. The filter used by interp is the same as the filter returned by intfilt.

  3. It applies the filter to the expanded input vector to produce the output.


[1] Digital Signal Processing Committee of the IEEE Acoustics, Speech, and Signal Processing Society, eds. Programs for Digital Signal Processing. New York: IEEE Press, 1979, chap. 8.

[2] Oetken, G., Thomas W. Parks, and H. W. Schüssler. “New results in the design of digital interpolators.” IEEE® Transactions on Acoustics, Speech, and Signal Processing. Vol. ASSP-23, 1975, pp. 301–309.

Introduced before R2006a

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