Separating a signal into its constituent components

1. How do you separate two signals?
2. Which algorithm is used to separate mixed signals from different sources?
3. What is the difference between PCA and ICA?
4. How does blind source separation work?

How do you separate two signals?

You can then get the separated signals by creating two copies (one for each component you want to recognize) of the Fourier-domain signal, zeroing unwanted Fourier coefficients (zeroing different sets of coefficients in each of the two copies), and reconstructing the two signals.

Which algorithm is used to separate mixed signals from different sources?

Single Channel Blind Source Separation (SCBSS) has had many algorithms for artificial mixed signal, where the number of mixing sources is assumed to be known, and mixed signal used in validation algorithm only contains two signal sources.

What is the difference between PCA and ICA?

PCA vs ICA

Specifically, PCA is often used to compress information i.e. dimensionality reduction. While ICA aims to separate information by transforming the input space into a maximally independent basis.

How does blind source separation work?

Blind Source Separation (BSS) refers to a problem where both the sources and the mixing methodology are unknown, only mixture signals are available for further separation process. In several situations it is desirable to recover all individual sources from the mixed signal, or at least to segregate a particular source.