Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 323

The DOI matches its Crossref record.

Analysis of time-varying signals with small BT values

Kodera, K., Gendrin, R., Villedary, C.·1978·IEEE Transactions on Acoustics, Speech, and Signal Processing

Abstract

We compare four different methods for analyzing time-varying signals, the frequency and amplitude of which are both varying (small BT signals, where B is the bandwidth and T the duration). All four methods give results which depend on the frequency bandwidth of the analyzing filter. But the modified moving window method (MMWM) (Kodera et al. [10]) is the one which gives the most significant result whatever the value of the filtering bandwidth. This is demonstrated both by a mathematical treatment and by a numerical simulation. In general, there are two characteristic curves in the frequency-time plane: one which gives the instantaneous frequency as a function of time and the other which gives the group delay time as a function of frequency. For signals with small BT values, these two curves are distinct and the different analyzing methods approach one or the other curve, or neither of them, depending on the bandwidth of the filtering window. The ability of each method to resolve multicomponent signals is discussed. The influence of the scaling factors used for the visualization of the signal in a two-dimensional plane is also studied.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/tassp.1978.1163047

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cited by

See all 323

Metadata

Authors
Kodera, K., Gendrin, R., & Villedary, C.
Venue
IEEE Transactions on Acoustics, Speech, and Signal Processing
Published
1978-02
Volume
26
Issue
1
Pages
64-76
ISSN
0096-3518 (ISSN-L)
OpenAlex
W2013454018
Cited by
323
References
0
FWCI
4.33
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: Analysis of time-varying signals with small BT values. https://app.cochat.ai/papers/10.1109/tassp.1978.1163047
The paper
Kodera, K., Gendrin, R., & Villedary, C. (1978). Analysis of time-varying signals with small BT values. IEEE Transactions on Acoustics, Speech, and Signal Processing. https://doi.org/10.1109/tassp.1978.1163047

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.