The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Data adaptive spectral analysis methods
Abstract
Two new methods (Maximum Likelihood Method or MLM, and Maximum Entropy Method or MEM) for power spectral density estimation have been experimentally investigated. Both methods, unlike conventional methods, adapt to the actual characteristics of the noise process under study. The new techniques are particularly valuable if the process contains one or more narrow peaks in frequency which are to be resolved. In this case, the output peaks from MEM are proportional to the square of the power in the narrow peaks but the area is equal to power. The peak values of the MLM reflect power directly. Both methods yield the true spectrum if the spectrum changes slowly enough with frequency. Neither of the new methods appears to be unduly sensitive to small statistical fluctuations of the estimated correlation function used to obtain spectral estimates.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An algorithm for the machine calculation of complex Fourier series
Cooley, J. W., & Tukey, J. W. (1965) · Mathematics of Computation · doi:10.1090/s0025-5718-1965-0178586-1 · Cited by 13,154
Maximum entropy spectral analysis
Burg, J. P. (1967) · Medical Entomology and Zoology · Cited by 2,046
Recursive solution to the multichannel filtering problem
Wiggins, R. A., & Robinson, E. A. (1965) · Journal of Geophysical Research · doi:10.1029/jz070i008p01885 · Cited by 369
Cited by
Two decades of array signal processing research: the parametric approach
Krim, H., & Viberg, M. (1996) · IEEE Signal Processing Magazine · doi:10.1109/79.526899 · Cited by 4,719
Hays, J. D., Imbrie, J., & Shackleton, N. J. (1976) · Science · doi:10.1126/science.194.4270.1121 · Cited by 3,781
Spectrum analysis—A modern perspective
Kay, S. M., & Marple, S. L. (1981) · Proceedings of the IEEE · doi:10.1109/proc.1981.12184 · Cited by 3,146
Godara, L. C. (1997) · Proceedings of the IEEE · doi:10.1109/5.622504 · Cited by 2,073
On robust Capon beamforming and diagonal loading
Li, J., Stoica, P., & Wang, Z. (2003) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2003.812831 · Cited by 1,439
Metadata
- Authors
- Lacoss, R. T.
- Venue
- Geophysics
- Publisher
- Society of Exploration Geophysicists
- Published
- 1971-08-01
- Volume
- 36
- Issue
- 4
- Pages
- 661-675
- ISSN
- 0016-8033 (ISSN-L)
- 1942-2156
- OpenAlex
- W2101928763
- Cited by
- 572
- References
- 3
- FWCI
- 14.73
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Data adaptive spectral analysis methods. https://app.cochat.ai/papers/10.1190/1.1440203
- The paper
- Lacoss, R. T. (1971). Data adaptive spectral analysis methods. Geophysics. https://doi.org/10.1190/1.1440203
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
