Signal Processing
A robust and computationally efficient subspace-based fundamental frequency estimator
IEEE Transactions on Audio, Speech, and Language Processing
Sinusoidal order estimation using angles between subspaces
EURASIP Journal on Advances in Signal Processing
Optimal filters for extraction and separation of periodic sources
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Optimal filter designs for separating and enhancing periodic signals
IEEE Transactions on Signal Processing
Helicopter radar return analysis: Estimation and blade number selection
Signal Processing
Entropy-based subspace separation for multiple frequency estimation
Digital Signal Processing
PEFAC - A Pitch Estimation Algorithm Robust to High Levels of Noise
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
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In this paper, we present a novel method for joint estimation of the fundamental frequency and order of a set of harmonically related sinusoids based on the multiple signal classification (MUSIC) estimation criterion. The presented method, termed HMUSIC, is shown to have an efficient implementation using fast Fourier transforms (FFTs). Furthermore, refined estimates can be obtained using a gradient-based method. Illustrative examples of the application of the algorithm to real-life speech and audio signals are given, and the statistical performance of the estimator is evaluated using synthetic signals, demonstrating its good statistical properties.