Abstract
When increasing numbers of principalcomponents are extracted by using the sequentialmethod proposed in [1] by Banour and Azimi-Sadjadi, the accumulated extractionerror will become dominant and affect the extractionsof the remaining principal components. To improvethis, we suggest that the initial weight vector forthe extraction of the next component should beorthogonal to the eigensubspace spanned by the alreadyextracted weight vectors. Simulation results showthat both the convergence and the accuracy of theextraction are improved. Our improved method is alsocapable of extracting full eigenspace accurately.
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Wong, A.SY., Wong, KW. & Wong, CS. A Practical Sequential Method for Principal Component Analysis. Neural Processing Letters 11, 107–112 (2000). https://doi.org/10.1023/A:1009646500088
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DOI: https://doi.org/10.1023/A:1009646500088