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Results for tag: "Signal Decomposition"

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction. Wind Energy Engineering - Product Thumbnail Image

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction. Wind Energy Engineering

  • Book
  • January 2020
Hybrid Intelligent Approaches for Smart Energy. Practical Applications. Edition No. 1. Next Generation Computing and Communication Engineering - Product Thumbnail Image

Hybrid Intelligent Approaches for Smart Energy. Practical Applications. Edition No. 1. Next Generation Computing and Communication Engineering

  • Book
  • October 2022
  • 336 Pages
  • 2 Results (Page 1 of 1)
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Signal Decomposition is a process used in electrical engineering to separate a signal into its constituent parts. It is used to analyze the frequency content of a signal, identify the components of a signal, and extract information from a signal. Signal decomposition can be used to identify the frequency components of a signal, such as the amplitude, phase, and frequency of each component. It can also be used to identify the source of a signal, such as a microphone or a speaker. Signal decomposition can also be used to identify the characteristics of a signal, such as its power spectrum, or to identify the presence of noise in a signal. Signal decomposition is used in a variety of applications, such as audio and video processing, communications, and control systems. Companies in the signal decomposition market include National Instruments, MathWorks, Keysight Technologies, and Anritsu. Show Less Read more