### Abstract

The Amplitude and Phase EStimation (APES) algorithm is a spectral estimation approach that estimates the complex amplitude of the power spectrum of a random process. Although its resolution performance has been observed to be slightly better than conventional FFT approaches, but quite inferior to super-resolution approaches like the Capon algorithm and MUSIC, no quantitative measure of resolution exists for the APES algorithm. This analysis provides a new exact two point measure of the large sample probability of resolution for the APES algorithm, as well as an approximation useful in capturing finite sample effects. This probability measure indicates that the APES algorithm resolution performance is fundamentally limited even in the limit of infinite signal-to-noise ratio (SNR).

Original language | English (US) |
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Title of host publication | 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Volume | IV |

ISBN (Print) | 0780388747, 9780780388741 |

DOIs | |

State | Published - Jan 1 2005 |

Externally published | Yes |

Event | 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States Duration: Mar 18 2005 → Mar 23 2005 |

### Other

Other | 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 |
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Country | United States |

City | Philadelphia, PA |

Period | 3/18/05 → 3/23/05 |

### Fingerprint

### ASJC Scopus subject areas

- Electrical and Electronic Engineering
- Signal Processing
- Acoustics and Ultrasonics

### Cite this

*2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions*(Vol. IV). [1416186] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2005.1416186

**On the probability of resolution for the amplitude and phase estimation (APES) spectral estimator.** / Richmond, Christ.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions.*vol. IV, 1416186, Institute of Electrical and Electronics Engineers Inc., 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05, Philadelphia, PA, United States, 3/18/05. https://doi.org/10.1109/ICASSP.2005.1416186

}

TY - GEN

T1 - On the probability of resolution for the amplitude and phase estimation (APES) spectral estimator

AU - Richmond, Christ

PY - 2005/1/1

Y1 - 2005/1/1

N2 - The Amplitude and Phase EStimation (APES) algorithm is a spectral estimation approach that estimates the complex amplitude of the power spectrum of a random process. Although its resolution performance has been observed to be slightly better than conventional FFT approaches, but quite inferior to super-resolution approaches like the Capon algorithm and MUSIC, no quantitative measure of resolution exists for the APES algorithm. This analysis provides a new exact two point measure of the large sample probability of resolution for the APES algorithm, as well as an approximation useful in capturing finite sample effects. This probability measure indicates that the APES algorithm resolution performance is fundamentally limited even in the limit of infinite signal-to-noise ratio (SNR).

AB - The Amplitude and Phase EStimation (APES) algorithm is a spectral estimation approach that estimates the complex amplitude of the power spectrum of a random process. Although its resolution performance has been observed to be slightly better than conventional FFT approaches, but quite inferior to super-resolution approaches like the Capon algorithm and MUSIC, no quantitative measure of resolution exists for the APES algorithm. This analysis provides a new exact two point measure of the large sample probability of resolution for the APES algorithm, as well as an approximation useful in capturing finite sample effects. This probability measure indicates that the APES algorithm resolution performance is fundamentally limited even in the limit of infinite signal-to-noise ratio (SNR).

UR - http://www.scopus.com/inward/record.url?scp=33646789871&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33646789871&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2005.1416186

DO - 10.1109/ICASSP.2005.1416186

M3 - Conference contribution

AN - SCOPUS:33646789871

SN - 0780388747

SN - 9780780388741

VL - IV

BT - 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions

PB - Institute of Electrical and Electronics Engineers Inc.

ER -