January 2019
Intermediate to advanced
294 pages
6h 43m
English
To find out what unmixing matrices are independent, we have to bank upon non-Gaussianity. Let's see how we can do this.
Here, we will need to maximize the kurtosis, which will turn the distribution into a non-Gaussian. This will result in independent components. The following diagram shows an image of fast ICA:

For this, we have the FastICA library in Python.
Let's look at how we can execute this in Python. We will work with the same Iris data. This might not be an ideal dataset for executing ICA, but this is being done for directional purposes. To execute the code in Python, we will need to perform the following steps:
Read now
Unlock full access