Downsampling a time-series AO

First we'll create a time-series of random white noise at 10Hz. To do that, define a plist with the key/value pairs shown below, and pass these to the ao constructor. If you're using the workbench, add an ao constructor block to the canvas and select the parameter set "From Time-series Function" and set the parameters as they are in the plist below.

    % create an AO of random data with fs = 10 Hz;
    pl      = plist('name', 'None', ...
                    'tsfcn',  'randn(size(t))', ...
                    'fs',      10, ...
                    'yunits', 'm', ...
                    'nsecs',   10);
    x       = ao(pl); % create AO
  

Now we will downsample this data by a factor 5 to 2Hz. We use the method ao/downsample and set the downsample factor in the plist as shown below.

    pl_down = plist('factor', 5); % add the decimation factor
    x_down  = downsample(x, pl_down); % downsample the input AO, x
    iplot(x, x_down) % plot original,x, and decimated,x_down, AOs
  

The downsample method takes an 'offset' key which controls where the counting starts. The default is to output every Nth sample starting with the first. The 'offset' key tells downsample to start the counting from a sample other than the first. The example below outputs every 4th sample starting from sample 10.

    pl_downoff = plist('factor', 4,'offset',10); % add decimation factor and offset parameter
    x_downoff  = downsample(x, pl_downoff); % downsample the input AO, x
    iplot(x, x_downoff) % plot original,x, and decimated,x_downoff, AOs
  

Topic 2 - Pre-processing of data

Upsampling a time-series AO

©LTP Team