![]() You see the Signal Analyzer app in the picture below with time, spectrum and panner axes enabled. The next three sounds are referred to as "moans". The first is commonly referred to as a "trill" and comprises roughly the first 10,000 samples. The recorded data includes four signal components of interest. ![]() In the picture below, after the app opens, I drag the signal x directly from the Workspace Browser (lower left section of the app) into the display region. whaleFile = fullfile(matlabroot, 'examples', 'matlab', '') I could have also done this by typing signalAnalyzer at the MATLAB prompt. In the code, I start the Signal Analyzer app from the APPS tab at the top of the MATLAB environment toolstrip. Note that you can use the command sound(x,fs) to listen to the audio. To start, I read the data into the MATLAB Workspace. The time scale in the data is compressed by a factor of 10 to raise the pitch and make the calls more audible. The file is from the library of animal vocalizations maintained by the Cornell University Bioacoustics Research Program. The file contains audio data from a Pacific blue whale. The short example below is based on what may be a familiar data set to you, a blue whale call. To demonstrate some of the new capabilities of the app, I have selected data that is easy to visualize and understand. You will find this to be very helpful in data analytics and machine learning applications where identifying patterns and trends, extracting features, and developing custom algorithms are key aspects of the workflow. You can gather insight with the app about the nature of your signals in the time and frequency domains simultaneously. We recently added Signal Analyzer app to the toolbox to make it really simple for you to visualize and compare multiple, time-based signals that live in the MATLAB Workspace. Signal Processing Toolbox provides functions and apps to preprocess, explore, and extract features from signals. You can now use these capabilities to gain insights into your data, which can help you to develop and validate your algorithms. In our recent releases, we have expanded the ability to analyze and compare signals in the time, frequency, and time-frequency domains. Signal Processing Toolbox has helped MATLAB users generate and work with signals for many years.
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