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Subspace-based Fundamental Frequency Estimation

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The problem of finding the fundamental frequency of a periodic waveform is important in many speech and audio processing systems with applications ranging from analysis and compression to separation and enhancement. In this talk, some new results on fundamental frequency estimation will be presented. Specifically, it will be shown how the subspace orthogonality property of the MUSIC algorithm can be used to estimate the fundamental frequency and the number of harmonics jointly. Also, the extension of the method to multiple periodic signals will be covered and ongoing research will be discussed.

This talk is part of the Signal Processing and Communications Lab Seminars series.

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