MATLAB: Signal Analysis in MATLAB

Name: MATLAB: Signal Analysis in MATLAB
Author: Gabriel Popoola

Start analyzing your signals for deeper insights

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Course: On-Demand

Hello, my name is Gabriel Papula. And this is the Signal Analysis in MATLAB module. During this module, we're going to discuss the Signal Analyzer, Signal Selection, Signal Pre-processing, Signal Exploration, and Analysis Sharing. During this lesson, I'm gonna go over some background information on the Signal Analyzer. As well as show you how to access the Signal Analyzer. The Signal Analyzer app is an interactive tool for visualizing, pre-processing, measuring, analyzing, and comparing Signals in the time domain, the frequency domain, and the time frequency domain. Using the app, you can access all the Signals in your MATLAB workspace. Smooth, filter, resample, detrend, denoise, duplicate, extract, rename, and edit Signals without leaving the app. You can add and apply custom pre-processing functions, visualize and compare multiple waveforms, spectrum persistence, spectrogram and scalogram, representations of Signals simultaneously and measure data and Signals statistics. The app provides a way to work with many Signals of varying durations at the same time and the same view. In order to use the Signal Analyzer app, you need to have the Wavelet Toolbox license. And, when you open up your apps, you should be able to go down to Signal Processing and Communications section. And here, you'll see a number of different Signal Processing and Communications applications. From Waveform Generator to a Signal Labeler to a Signal Analyzer. And so, just to show you something, if you type in Signal Analyzer. What you'll see, are you have a Mix Signal Analyzer. Which allows you to analyze and visualize mix Signal simulation data, trends and waveforms. And you have the Signal Analyzer. Which allows you to view, analyze and compare Signals. I don't want you to get these two mixed up. What we're talking about here is this Signal Analyzer. And just to give you a brief overview of what it looks like, I'm going to go ahead and open it up. And now we have various toolbars. We have the Analyzer. Which has File, Layout, Signal Table, Pre-processing and other options. Then you have Display. Which has a Display Options menu, Cursors, Zoom & Pan, Views, Region of Interest and Time Limits. Then you have the Time, which has options to normalize your axis and show markers. And then you have Time Limits. And then Axis Limits. Then lastly, you have Measures. Which allows you to to configure Cursors, Calculate different Signal Statistics and then set your Time Limits. This concludes this lesson. Thank you.

Advanced Provider : Gabriel Popoola 5 Lessons · 31m in Arabic, German, English, Spanish, French, Portuguese, Chinese

Course Description

Signal analysis is a vital part of time-series analysis, forecasting systems, and even some predictive systems. You will learn how to utilize a signal analyzer app, which is an interactive tool for visualizing, pre-processing, measuring, analyzing, and comparing signals in the time domain, the frequency domain, and the time-frequency domain. There are a variety of functions and algorithms that can be applied to your signals during the signal analysis process. The Signal Analyzer App in MATLAB combines many of these into one location. In this MATLAB module, you will learn about how to use the Signal Analyzer App for your signal analysis needs.

After completing this module, you will be able to apply what you learned to any project or task involving signal analysis. You will learn how to share your analysis with other individuals, whether it be researchers or stakeholders, depending on the application of the work that you're doing. This can be useful in any area where time-series data or continuous signals are used. Specific areas and industries include music, audio analysis, and seismology.

What You'll Learn

Explain the concept of signal analysis and its role in time-series analysis, forecasting, and predictive systems
Use the Signal Analyzer App to visualize, pre-process, measure, analyze, and compare signals in the time, frequency, and time-frequency domains
Describe the Signal Analyzer App workflow, including signal selection, preprocessing, and exploration
Apply functions and algorithms available in the Signal Analyzer App to your own signals
Share your signal analysis with researchers or stakeholders

Key Takeaways

Signal analysis is a vital part of time-series analysis, forecasting systems, and some predictive systems.
The Signal Analyzer App is an interactive tool for visualizing, pre-processing, measuring, analyzing, and comparing signals in the time domain, the frequency domain, and the time-frequency domain.
The Signal Analyzer App combines many signal analysis functions and algorithms into one location.
Signal analysis is useful in any area where time-series data or continuous signals are used, including music, audio analysis, and seismology.
Completing this module enables you to share your analysis with others, such as researchers or stakeholders, depending on the application.

Frequently Asked Questions

What will I learn in this MATLAB signal analysis course?

You will learn how to use the Signal Analyzer App in MATLAB to visualize, pre-process, measure, analyze, and compare signals in the time domain, the frequency domain, and the time-frequency domain, as well as how to share your analysis with others.

Who is this course useful for?

It is useful for anyone working in areas where time-series data or continuous signals are used, with specific areas and industries including music, audio analysis, and seismology.

What topics do the lessons cover?

The lessons cover the Signal Analyzer, signal selection, signal preprocessing, signal exploration, and analysis sharing.

What skills does this course help develop?

It helps develop skills in Analytic Applications, Audio Analyzer, MATLAB, Signal Processing, Spectral Analysis, and Spectrum Analyzer.

What will I be able to do after completing this module?

After completing this module, you will be able to apply what you learned to any project or task involving signal analysis and share your analysis with researchers or stakeholders.