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Independent Component Analysis ICA

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nurin noor
nurin noor el 8 de Jun. de 2021
Respondida: Prasanna el 21 de Mayo de 2024
Hi everyone, I need help with ICA
I noticed that there are some methods such as RICA, jadeR function. I am not sure which one is the best method to apply ICA after feature extraction. I tried using jadeR
NumberIC = 3; % number of Independant components we are interested in
FeatureICA = FeatureSignal'; % Cumputing the ICA using the jadeR function
W = jader(FeatureICA,NumberIC);
ICAFinal = (W*FeatureICA)';
These are code i found online, but the third line W = jader(FeatureICA,NumberIC); giving Undefined function 'jadeR' for input arguments of type 'double'. error. Please help me. I dont undersand ICA.

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Prasanna
Prasanna el 21 de Mayo de 2024
Hi,
The error message you're encountering, "Undefined function 'jadeR' for input arguments of type 'double'", suggests that MATLAB does not recognize the jadeR function. This typically happens for one of two reasons: either the function is not included in your MATLAB path, or the necessary toolbox or package that includes 'jadeR' is not installed. You can use the jadeR script included in the list of documentation links provided below in the answer to call the ‘jadeR’ function.
Independent Component Analysis (ICA) is a computational method for separating a multivariate signal into additive, independent components. It's commonly used for signal processing tasks such as feature extraction, noise reduction, and source separation.
Regarding the choice of ICA method (e.g., RICA, jadeR), the best method can depend on the specifics of your data and your project requirements. RICA (Reconstruction ICA) is available directly within MATLAB's Machine Learning and Deep Learning Toolboxes and can be a good starting point due to its integration and support within MATLAB. JADE (Joint Approximate Diagonalization of Eigenmatrices) is another popular ICA algorithm known for its efficiency and effectiveness in many scenarios but might require an external implementation or toolbox in MATLAB.
For more information on the functions, refer to the following documentations:
Hope this helps.

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