Computationally efficient parameter estimation for harmonic sinusoidal signals
Signal Processing - Special issue on current topics in adaptive filtering for hands-free acoustic communication and beyond
Signal Processing
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
A robust and computationally efficient subspace-based fundamental frequency estimator
IEEE Transactions on Audio, Speech, and Language Processing
Multi-Pitch Estimation
Joint High-Resolution Fundamental Frequency and Order Estimation
IEEE Transactions on Audio, Speech, and Language Processing
Hi-index | 0.08 |
In this paper, we present an iterative method for estimation of pitches from signals containing multiple sources using subspace techniques. The resulting estimator is termed Iterative Harmonic MUltiple SIgnal Classification (I-HMUSIC). Different modifications of I-HMUSIC are proposed that improve upon the classical MUSIC algorithm, including a computationally efficient method for noise subspace updating I-HMUSIC and its modifications are evaluated and compared with both the Cramer-Rao lower bound (CRLB) and non-iterative HMUSIC; good statistical performances have been obtained.