Joint Principal Component Analysis and Supervised k Means Algorithm via Non-Iterative Analytic Optimization Approach

• Published in: IEEE transactions on signal processing Vol. 72; pp. 1348 - 1360
• Main Authors: Zhang, Zhanbin, Ling, Bingo Wing-Kuen, Huang, Guoheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Arithmetic; Classification; Classification algorithms; Clusters; EEG; Exact solutions; Joint PCA and supervised k means algorithm; Mathematical analysis; Matrices (mathematics); mental arithmetic classification; non-iterative analytic optimization; Optimization; Principal component analysis; Principal components analysis; Reduction; Signal processing algorithms; singular value decomposition; Symmetric matrices; symmetric matrix; Transforms

It is worth noting that the traditional methods for performing both the dimensional reduction and the classification are via the two steps iterative approaches. In this case, performing the dimensional reduction does not consider the classification. On the other hand, the classification is performed...