LTPDA Toolbox™ contents Upsampling a time-series AO   Interpolation of a time-series AO

Resampling a time-series AO

Resampling is the process of changing the sampling rate of data. The method ao/resample changes the sampling rate of the input AOs to the desired output sampling frequency by performing band-limited interpolation, or interpolation.

If the ratio of the input and the desired output sample rate can be expressed as an integer ratio P/Q where both P and Q then band-limited interpolation can be performed. In this case, the data-series is upsampled (by inserting zeros) and then a low-pass filter is applied at the original Nyquist frequency.

The ao/resample method can be called with the syntax: 

    b = resample(a, pl)

and can accept the following parameters:

Key Description

FSOUT

The desired output frequency (must be positive and integer)

FILTER

The filter to apply in the resampling process

Example 1

Here we will resample a sequence of random data from the original sampling rate of 1 Hz to an output sampling rate of 50 Hz. 

    pl    = plist('name', 'None', 'tsfcn', 'randn(size(t))', 'nsecs', 100, 'fs', 1, 'yunits', 'm');
    x     = ao(pl)
    pl_re = plist('fsout', 50);
    x_re  = resample(x, pl_re); % resample the input AO (x) to obtain the resampled output AO (y)
    iplot(x, x_re, plist('XRanges', [10 20], ...
                         'Markers', {'o', '.'}, ...
                         'LineStyles', {'-', 'none'})) % plot original and resampled data
Resample


Upsampling a time-series AO  Upsampling a time-series AO   Interpolation of a time-series AO Interpolation of a time-series AO

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