sinc
Sinc function
Syntax
Description
Examples
Ideal Bandlimited Interpolation
Perform ideal bandlimited interpolation of a random signal sampled at integer spacings.
Assume that the signal to interpolate, x
, is 0 outside of the given time interval and has been sampled at the Nyquist frequency. Reset the random number generator for reproducibility.
rng default t = 1:10; x = randn(size(t))'; ts = linspace(-5,15,600); [Ts,T] = ndgrid(ts,t); y = sinc(Ts - T)*x; plot(t,x,'o',ts,y) xlabel Time, ylabel Signal legend('Sampled','Interpolated','Location','SouthWest') legend boxoff
Input Arguments
x
— Input array
scalar value | vector | matrix | N-D array
Input array, specified as a real-valued or complex-valued scalar, vector,
matrix, or N-D array. When x
is
nonscalar, sinc
is an element-wise operation.
Data Types: single
| double
Complex Number Support: Yes
Output Arguments
y
— Sinc of input
scalar value | vector | matrix | N-D array
Sinc of the input array, x
, returned as a real-valued
or complex-valued scalar, vector, matrix, or N-D array of
the same size as x
.
More About
sinc
The sinc function is defined by
This analytic expression corresponds to the continuous inverse Fourier transform of a rectangular pulse of width 2π and height 1:
The space of functions bandlimited in the frequency range is spanned by the countably infinite set of sinc functions shifted by integers. Thus, you can reconstruct any such bandlimited function g(t) from its samples at integer spacings:
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
The
sinc
function fully supports tall arrays. For more information,
see Tall Arrays.
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Thread-Based Environment
Run code in the background using MATLAB® backgroundPool
or accelerate code with Parallel Computing Toolbox™ ThreadPool
.
This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Version History
Introduced before R2006a
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