Which algorithm is commonly used for blind source separation or separating mixed signals?
- Principal Component Analysis (PCA)
- Support Vector Machine (SVM)
- K-Means Clustering
- Decision Trees
Principal Component Analysis (PCA) is commonly used for blind source separation, reducing the dimensionality of data to separate mixed signals. PCA identifies the principal components or directions of maximum variance in the data.
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