Write data to buffer
Write Variable Frame Sizes to Buffer
Write a sine wave of variable frame size to the buffer. Compute the FFT of the sine wave and visualize the result on an array plot.
dsp.FFT System objects.
asynBuff = dsp.AsyncBuffer; plotter = dsp.ArrayPlot; fftObj = dsp.FFT('FFTLengthSource','Property','FFTLength',256);
The sine wave is generated using the
sin function in MATLAB. The
finish variables mark the start and finish indices of each frame. If enough data is cached, read from the buffer and perform the FFT. View the FFT on an array plot.
start = 1; for Iter = 1 : 2000 numToWrite = randi([200,800]); finish = start + numToWrite; inputData = sin(start:finish)'; start = finish + 1; write(asynBuff,inputData); while asynBuff.NumUnreadSamples >= 256 x = read(asynBuff,256); X = abs(fftObj(x)); plotter(log(X)); end end
asyncBuff — Async buffer
Async buffer, specified as a
x — Data input
vector | matrix
Data written to the buffer, specified as a vector or a matrix. The maximum number of
rows in the buffer is determined by the
Capacity property of
asyncBuff. The number of channels in the buffer is determined by
the second dimension of the first data written to the buffer. Successive data inputs can
vary in the number of rows, but the number of channels must remain fixed. To change the
number of channels, you must call
release on the buffer.
For example, the following is accepted:
asyncBuff = dsp.AsyncBuffer; % First call to write write(asyncBuff,randn(15,5)); % Add more data with a different number of rows write(asyncBuff,randn(25,5)); write(asyncBuff,randn(5,5));
The following is not accepted and errors out:
asyncBuff = dsp.AsyncBuffer; % First call to write write(asyncBuff,randn(15,5)); % Add more data with a different number of columns write(asyncBuff,randn(15,15));
To change the number of channels, call
release on the
asyncBuff = dsp.AsyncBuffer; % First call to write write(asyncBuff,randn(15,5)); release(asyncBuff) % Add more data with a different number of columns write(asyncBuff,randn(15,15));
Complex Number Support: Yes
nOverrun — Number of samples overrun
Number of samples overrun in the current call to
write. The number of samples overrun is the number of unread samples
x is a multichannel input, then
nOverrun is the number of rows of data overrun.
Introduced in R2017a