ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help


Nagesh, Sudarshan and Mulleti, Satish and Seelamantula, Chandra Sekhar (2014) ON THE ROLE OF THE HILBERT TRANSFORM IN BOOSTING THE PERFORMANCE OF THE ANNIHILATING FILTER. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), MAY 04-09, 2014, Florence, ITALY.

[img] PDF
int_con_aco_spe_sig_pro_2014.pdf - Published Version
Restricted to Registered users only

Download (134kB) | Request a copy
Official URL: http://dx.doi.org/ 10.1109/ICASSP.2014.6853916


We consider the problem of parameter estimation from real-valued multi-tone signals. Such problems arise frequently in spectral estimation. More recently, they have gained new importance in finite-rate-of-innovation signal sampling and reconstruction. The annihilating filter is a key tool for parameter estimation in these problems. The standard annihilating filter design has to be modified to result in accurate estimation when dealing with real sinusoids, particularly because the real-valued nature of the sinusoids must be factored into the annihilating filter design. We show that the constraint on the annihilating filter can be relaxed by making use of the Hilbert transform. We refer to this approach as the Hilbert annihilating filter approach. We show that accurate parameter estimation is possible by this approach. In the single-tone case, the mean-square error performance increases by 6 dB for signal-to-noise ratio (SNR) greater than 0 dB. We also present experimental results in the multi-tone case, which show that a significant improvement (about 6 dB) is obtained when the parameters are close to 0 or pi. In the mid-frequency range, the improvement is about 2 to 3 dB.

Item Type: Conference Proceedings
Series.: International Conference on Acoustics Speech and Signal Processing ICASSP
Publisher: IEEE
Additional Information: Copyright for this article belongs to the IEEE, USA.
Keywords: Annihilating filter; discrete Hilbert transform; finite rate of innovation; sampling; spectral estimation
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 12 Jan 2015 06:57
Last Modified: 12 Jan 2015 06:57
URI: http://eprints.iisc.ac.in/id/eprint/50608

Actions (login required)

View Item View Item