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Results for tag: "Blind Source Separation"

Digital Signal Processing with Kernel Methods. Edition No. 1. IEEE Press - Product Thumbnail Image

Digital Signal Processing with Kernel Methods. Edition No. 1. IEEE Press

  • Book
  • January 2018
  • 672 Pages
Source Separation and Machine Learning - Product Thumbnail Image

Source Separation and Machine Learning

  • Book
  • October 2018
  • 2 Results (Page 1 of 1)
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Blind Source Separation (BSS) is a field of electrical engineering that focuses on the separation of signals from multiple sources. It is used to separate a mixture of signals into its individual components, without prior knowledge of the source signals. BSS is used in a variety of applications, such as audio signal processing, medical imaging, and communications. It is also used to improve the performance of signal processing algorithms. BSS algorithms are based on statistical models and signal processing techniques, such as Independent Component Analysis (ICA), Principal Component Analysis (PCA), and Non-Negative Matrix Factorization (NMF). These algorithms are used to identify the source signals and separate them from the mixture. BSS is an important tool for signal processing and has been used in a variety of applications, such as speech recognition, image processing, and biomedical signal processing. Some companies in the Blind Source Separation market include IBM, Microsoft, Google, Apple, and Qualcomm. Show Less Read more