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Fig. 11 | EURASIP Journal on Advances in Signal Processing

Fig. 11

From: Class-specific discriminant time-frequency analysis using novel jointly learnt non-negative matrix factorization

Fig. 11

The JLNMF method was applied to two signals: one from a normal and one form a pathological voice subject. a A 0.5-s segment of a normal subject. b TF signal of the segment shown in (a). c A 0.5-s segment of a pathological voice disorder subject. d The TF signal of the pathological subject shown in (c). e Normal-specific TF bases. f Pathological-specific TF bases. g Shared-TF bases

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