MATLAB | Spectral and Synchronous Averaging @MATLAB | Uploaded August 2024 | Updated October 2024, 1 week ago.
Watch this sequel on signal averaging in Simulink® to learn about extensions of the techniques covered in “The Many Ways to Average a Signal.” youtu.be/EIlH6-lA-Bo
Specifically, learn how to combine running, exponential, sliding, and weighted moving averages in unique ways that lead to novel averaging approaches such as the triple exponent moving average and the Hull moving average. You’ll also see how these same averaging techniques are applied in the frequency domain to power spectrums using the Simulink Spectrum Estimator and Spectrum Analyzer blocks.
Get started now by downloading the examples in this demonstration on GitHub®: github.com/kschutz68/AVERAGING_1.git
Learn more:
- Moving Average: bit.ly/3W1Qi3y
- dsp.MovingAverage: bit.ly/3L3oANp
- Spectrum Analyzer: bit.ly/3XG32xS
Chapters:
00:00 Introduce Different Types of Signal Averaging
02:10 Walkthrough of a Running Average Implementation
03:46 Test Running Average Model
05:38 Brute-Force Moving Average Implementation
08:55 Efficient Vectorized Delay Line–Based Moving Average Implementation
10:10 FIR-Based Moving Average Implementation
10:30 CIC-Based Moving Average Implementation
11:30 Moving Average from Sliding Window in DSP System Toolbox
12:10 Using the Scope Legend to Turn Traces On and Off
12:34 Walkthrough of the Fixed-Coefficient Exponential Averaging Approach
14:22 Walkthrough of the Dynamic-Coefficient Exponential Averaging Approach
16:15 Exponential Averaging Block Implementation from DSP System Toolbox
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Learn more about MATLAB: goo.gl/8QV7ZZ
Learn more about Simulink: goo.gl/nqnbLe
See what's new in MATLAB and Simulink: goo.gl/pgGtod
© 2024 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
Watch this sequel on signal averaging in Simulink® to learn about extensions of the techniques covered in “The Many Ways to Average a Signal.” youtu.be/EIlH6-lA-Bo
Specifically, learn how to combine running, exponential, sliding, and weighted moving averages in unique ways that lead to novel averaging approaches such as the triple exponent moving average and the Hull moving average. You’ll also see how these same averaging techniques are applied in the frequency domain to power spectrums using the Simulink Spectrum Estimator and Spectrum Analyzer blocks.
Get started now by downloading the examples in this demonstration on GitHub®: github.com/kschutz68/AVERAGING_1.git
Learn more:
- Moving Average: bit.ly/3W1Qi3y
- dsp.MovingAverage: bit.ly/3L3oANp
- Spectrum Analyzer: bit.ly/3XG32xS
Chapters:
00:00 Introduce Different Types of Signal Averaging
02:10 Walkthrough of a Running Average Implementation
03:46 Test Running Average Model
05:38 Brute-Force Moving Average Implementation
08:55 Efficient Vectorized Delay Line–Based Moving Average Implementation
10:10 FIR-Based Moving Average Implementation
10:30 CIC-Based Moving Average Implementation
11:30 Moving Average from Sliding Window in DSP System Toolbox
12:10 Using the Scope Legend to Turn Traces On and Off
12:34 Walkthrough of the Fixed-Coefficient Exponential Averaging Approach
14:22 Walkthrough of the Dynamic-Coefficient Exponential Averaging Approach
16:15 Exponential Averaging Block Implementation from DSP System Toolbox
--------------------------------------------------------------------------------------------------------
Get a free product trial: goo.gl/ZHFb5u
Learn more about MATLAB: goo.gl/8QV7ZZ
Learn more about Simulink: goo.gl/nqnbLe
See what's new in MATLAB and Simulink: goo.gl/pgGtod
© 2024 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
