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Data analysis is very important for signal processing
applications
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PCA is an effective data normalization technique
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Choice of LDA type is application dependent
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Class-dependent LDA type proved to be better with an average
of 50.41 % error rate over the class-independent LDA type when
applied on image database
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Overall error rate of 39.7% using PCA proved to be better
compared to LDA on a 43 feature vector