Blind source separation python

1. What is blind source separation problem?
2. What is blind source separation in machine learning?
3. What is source separation approach?
4. How do you perform ICA?

What is blind source separation problem?

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.

What is blind source separation in machine learning?

3.3 BSS and its application in BCI

BSS refers to a problem where the sources and the mixing matrix are indistinct and only observation signals are available for the separation procedure. The objective is to separate unknown and independent sources using observation signals.

What is source separation approach?

Source separation, blind signal separation (BSS) or blind source separation, is the separation of a set of source signals from a set of mixed signals, without the aid of information (or with very little information) about the source signals or the mixing process.

How do you perform ICA?

To perform ICA, we can use fastICA R package. We have to install fastICA package in R or R studio. A data matrix with n rows representing observations and p columns representing variables. Number of components to be extracted.