Why do we need non Gaussian ICA?

Thus ICA is built on using the assumption of non-Gaussianality in the latent factors to tease them apart. If more than one underlying factor is Gaussian then they will not be separated by ICA since the separation is based on deviation from normality.

What is kurtosis in ICA?

maximizing statistical independence between components in some way – one method used is to maximize non-gaussianity (kurtosis). That being said, ICA assumes that the multivariate signal is a mixture of independent, non-gaussian components, so I understand that independence is assumed in the model.

What is mixing matrix in ICA?

The mixing matrix is the parameter of interest, and its columns are assumed to be linearly independent such that it is invertible. 2. The source signals s j ( t ) ( j = 1 , … , N ) are mutually statistically independent signals.

What is nonlinear ICA?

Nonlinear ICA is a fundamental problem for unsupervised representation learning, emphasizing the capacity to recover the underlying latent variables generating the data (i.e., identifiability).

What does Leptokurtic distribution indicate?

A leptokurtic distribution means that the investor can experience broader fluctuations (e.g., three or more standard deviations from the mean) resulting in greater potential for extremely low or high returns.

What is Fast independent component analysis?

FastICA is an efficient and popular algorithm for independent component analysis invented by Aapo Hyvärinen at Helsinki University of Technology.

Is ICA a machine learning?

Independent Component Analysis (ICA) is a machine learning technique to separate independent sources from a mixed signal. Unlike principal component analysis which focuses on maximizing the variance of the data points, the independent component analysis focuses on independence, i.e. independent components.

What is ICA quality?

Purpose: Independent component analysis (ICA) is an established method of analyzing human functional MRI (fMRI) data. Here, an ICA-based fMRI quality control (QC) tool was developed and used.