On a fast digital method of estimating the autocorrelation of a gaussian stationary process
Abstract
The zero-mean stationary Gaussian processes have the property that if they are input into an instantaneous nonlinear device, the cross correlation of input and output is proportional to the auto-correlation of the input. This suggests an estimation procedure for the autocorrelation function based mainly on additions, which is a modified type of the PCC (polarity coincidence correlator). The object of this paper is to compute the bias and the variance of such an estimator and to discuss some fundamental properties. As a reference, some examples are provided which compare the behavior of the modified PPC estimator to the classical one based on products and additions.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Cites
Mathematical Methods of Statistics.
Geary, R. C., & Cramer, H. L. (1947) · The Economic Journal · doi:10.2307/2226151 · Cited by 6,095 · see citing works
Spectral Analysis and its Applications.
Freiberger, W. F., Jenkins, G. M., & Watts, D. G. (1969) · Journal of the American Statistical Association · doi:10.2307/2286100 · Cited by 4,990 · see citing works
Theory and application of the separable class of random processes
Nuttall, A. H. (1958) · Cited by 94 · see citing works
A fast digital method of estimating the autocorrelation of a Guassian stationary process
Hertz, D. (1982) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/tassp.1982.1163885 · Cited by 19 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Discrete time techniques for time delay estimation
Jacovitti, G., & Scarano, G. (1993) · IEEE Transactions on Signal Processing · doi:10.1109/78.193195 · Cited by 433 · see citing works
Self-citationTime Delay Estimation in Room Acoustic Environments: An Overview
Chen, J., Benesty, J., & Huang, Y. (2006) · EURASIP Journal on Advances in Signal Processing · doi:10.1155/asp/2006/26503 · Cited by 370 · see citing works
Adaptive algorithms with an automatic gain control feature
Shan, T., & Kailath, T. (1988) · IEEE Transactions on Circuits and Systems · doi:10.1109/31.1709 · Cited by 131 · see citing works
Performance of GCC- and AMDF-Based Time-Delay Estimation in Practical Reverberant Environments
Chen, J., Benesty, J., & Huang, Y. (. (2005) · EURASIP Journal on Advances in Signal Processing · doi:10.1155/asp.2005.25 · Cited by 67 · see citing works
Methods for estimating the autocorrelation function of complex Gaussian stationary processes
Jacovitti, G., Neri, A., & Cusani, R. (1987) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/tassp.1987.1165253 · Cited by 53 · see citing works
Self-citationEfficient tracking of the cross-correlation coefficient
Aarts, R. M., Irwan, R., & Janssen, A. J. E. M. (2002) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/tsa.2002.803447 · Cited by 31 · see citing works
Cumulant Series Expansion of Hybrid Nonlinear Moments of /et
Scarano, G., Caggiati, D., & Jacovitti, G. (1993) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.1993.193184 · Cited by 27 · see citing works
Self-citationKoh, T., & Powers, E. J. (1985) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/tassp.1985.1164623 · Cited by 24 · see citing works
Comparison of three correlation coefficient estimators for gaussian stationary processes
Gabriel, K. J. (1983) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/tassp.1983.1164166 · Cited by 22 · see citing works
Subband DFT — Part I: Definition, interpretation and extensions
Shentov, O. V., Mitra, S. K., Heute, U., & Hossen, A. (1995) · Signal Processing · doi:10.1016/0165-1684(94)00103-7 · Cited by 21 · see citing works
Generalized Random Decrement Method for Analysis of Vibration Data
Spanos, P. D., & Zeldin, B. A. (1998) · Journal of vibration and acoustics · doi:10.1115/1.2893901 · Cited by 19 · see citing works
An efficient technique for high correlation estimation
Jacovitti, G., & Cusani, R. (1987) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1987.1165195 · Cited by 15 · see citing works
Self-citationThrone, R. D. (1993) · Computers in Biology and Medicine · doi:10.1016/0010-4825(93)90086-g · Cited by 12 · see citing works
Performances of the hybrid-sign correlation coefficient estimator for Gaussian stationary processes
Jacovitti, G., & Cusani, R. (1985) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/tassp.1985.1164614 · Cited by 10 · see citing works
Self-citationEfficient autocorrelation estimation using relative magnitudes
Sullivan, M. C. (1989) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/29.21717 · Cited by 10 · see citing works
An Analysis of a Near-End Crosstalk Cancelation System That Uses Adaptive Filters
Nongpiur, R. C., Shpak, D. J., & Antoniou, A. (2008) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2008.924871 · Cited by 7 · see citing works
Correlation estimators based on simple nonlinear transformations
Sullivan, M. C., & Wegman, E. J. (1995) · IEEE Transactions on Signal Processing · doi:10.1109/78.388856 · Cited by 7 · see citing works
Applicability of the relay correlator to radar signal processing
Cacopardi, S. (1983) · Electronics Letters · doi:10.1049/el:19830491 · Cited by 6 · see citing works
Near-end crosstalk cancellation in xDSL systems
Nongpiur, R. C., Shpak, D. J., & Antoniou, A. (2003) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/acssc.2002.1197213 · Cited by 5 · see citing works
Cusani, R., & Neri, A. (1985) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/tassp.1985.1164695 · Cited by 5 · see citing works
Self-citationNeural correlation based on the IPFM model
Giunta, G., & Neri, A. (1990) · IEEE Transactions on Systems Man and Cybernetics · doi:10.1109/21.47828 · Cited by 4 · see citing works
Self-citationA note on the computational complexity of high correlation estimators
Giunta, G. (1991) · IEEE Transactions on Signal Processing · doi:10.1109/78.80834 · Cited by 3 · see citing works
Adaptive Filtering Algorithms With Automatic Gain Control
Shan, T., & Kailath, T. (1985) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/acssc.1985.671512 · Cited by 3 · see citing works
Reduced complexity variable precision signal processing for digital communications
Marino, C. S., & Chau, P. M. (2003) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/acssc.1999.831937 · Cited by 2 · see citing works
Efficient maximum entropy spectral estimation using non-multiplication methods
Koh, T., & Powers, E. J. (2005) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1984.1172311 · Cited by 1 · see citing works
Complex autocorrelation estimators in radar signal processing
Barbarossa, S., Capece, M., & Picardi, G. (1985) · Electronics Letters · doi:10.1049/el:19850530
Fibre Optic Sensor for Speed Measurement
Gogoasa, I. (1996) · Victoria University Research Repository (Victoria University)
- Authors
- Jacovitti, G., Neri, A., & Cusani, R.
- Affiliations
- Sapienza University of Rome (IT)
- ORCID
- Venue
- IEEE Transactions on Acoustics, Speech, and Signal Processing
- Published
- 1984-10
- Volume
- 32
- Issue
- 5
- Pages
- 968-976
- ISSN
- 0096-3518 (ISSN-L)
- OpenAlex
- W2103588339
- Cited by
- 27
- References
- 4
- FWCI
- 3.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Acoustics Speech and Signal Processing (publishedVersion)
- IRIS Research product catalog (Sapienza University of Rome) (submittedVersion)
- Iris (Roma Tre University) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Computational Mechanics › Advanced Adaptive Filtering Techniques
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Signal Processing Techniques
- Physical Sciences › Computer Science › Signal Processing › Digital Filter Design and Implementation
- Keywords
- autocorrelation estimation, stationary Gaussian processes, nonlinear devices, estimation bias, estimator variance, digital signal processing, cross correlation function
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
