The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Improved time-frequency representation of multicomponent signals using exponential kernels
Abstract
The authors introduce a time-frequency distribution of L. Cohen's (1966) class and examines its properties. This distribution is called exponential distribution (ED) after its exponential kernel function. First, the authors interpret the ED from the spectral-density-estimation point of view. They then show how the exponential kernel controls the cross terms as represented in the generalized ambiguity function domain, and they analyze the ED for two specific types of multicomponent signals: sinusoidal signals and chirp signals. Next, they define the ED for discrete-time signals and the running windowed exponential distribution (RWED), which is computationally efficient. Finally, the authors present numerical examples of the RWED using the synthetically generated signals. It is found that the ED is very effective in diminishing the effects of cross terms while retaining most of the properties which are useful for a time-frequency distribution.>
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
Some features of time-frequency representations of multicomponent signals
Flandrin, P. (2005) · ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing · doi:10.1109/icassp.1984.1172741 · Cited by 239
Cited by
Linear and quadratic time-frequency signal representations
Hlawatsch, F., & Boudreaux-Bartels, G. F. (1992) · IEEE Signal Processing Magazine · doi:10.1109/79.127284 · Cited by 1,632
Goyal, D., & Pabla, B. S. (2016) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-015-9145-0 · Cited by 508
A basis for efficient representation of the S-transform
Stockwell, R. G. (2007) · Digital Signal Processing · doi:10.1016/j.dsp.2006.04.006 · Cited by 417
Linear frequency-modulated signal detection using Radon-ambiguity transform
Wang, M., Chan, A. K., & Chui, C. K. (1998) · IEEE Transactions on Signal Processing · doi:10.1109/78.661326 · Cited by 257
Condition based maintenance of machine tools—A review
Goyal, D., & Pabla, B. S. (2015) · CIRP Journal of Manufacturing Science and Technology · doi:10.1016/j.cirpj.2015.05.004 · Cited by 175
Metadata
- Authors
- Choi, H.-I., & Williams, W. J.
- Venue
- IEEE Transactions on Acoustics, Speech, and Signal Processing
- Published
- 1989-06
- Volume
- 37
- Issue
- 6
- Pages
- 862-871
- ISSN
- 0096-3518 (ISSN-L)
- OpenAlex
- W2150391795
- Cited by
- 1,299
- References
- 1
- FWCI
- 36.11
- 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: Improved time-frequency representation of multicomponent signals using exponential kernels. https://app.cochat.ai/papers/10.1109/assp.1989.28057
- The paper
- Choi, H.-I., & Williams, W. J. (1989). Improved time-frequency representation of multicomponent signals using exponential kernels. IEEE Transactions on Acoustics, Speech, and Signal Processing. https://doi.org/10.1109/assp.1989.28057
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.
