Daubechies, Ingrid; Planchon, Fabrice Adaptive Gabor transforms. (English) Zbl 1032.94001 Appl. Comput. Harmon. Anal. 13, No. 1, 1-21 (2002). Consider a family of Gaussian windows \(g^{\beta, \delta}(x) = \delta^{1/4} e^{i(\beta/2)x^2 - \delta x^2}\). In this paper the authors study generalized \((\beta, \delta)\)-Gabor tansforms, which are defined as \(G^{\beta, \delta} (f) (p,q) = \int g^{\bar \beta, \delta}_{p,q}(x)f(x) dx\), where \(g^{\beta, \delta}_{p,q}(x) = e^{ipx-pq/2}g^{\beta, \delta}(x-q)\). Based on these representations, the authors provide various adaptive Gabor transforms for analysis of one-dimensional signals by appropriately picking window functions from the family \(g^{\beta, \delta}\). The algorithms for choosing the best windows are computationally efficient, and multiple examples are provided. Reviewer: Wojciech Czaj (Wroclaw) Cited in 2 Documents MSC: 94A11 Application of orthogonal and other special functions 94A12 Signal theory (characterization, reconstruction, filtering, etc.) 42C40 Nontrigonometric harmonic analysis involving wavelets and other special systems 42C15 General harmonic expansions, frames Keywords:Gabor transform; Wigner-Ville transform; adaptive time-frequency analysis Software:Time-frequency Toolbox × Cite Format Result Cite Review PDF Full Text: DOI References: [1] Akan, A.; Chaparro, L., Evolutionary spectral analysis using a warped Gabor expansion, (IEEE ICASSP96, Atlanta (1996)) · Zbl 0985.94003 [2] Andrieux, J. C., Optimum smoothing of the Wigner-Ville distribution, IEEE Trans. Signal Process., ASSP-35, 6, 764-769 (1987) [3] Auger, F.; Flandrin, P.; Gonçalvès, P.; Lemoine, O., Time-Frequency Toolbox [4] Baraniuk, R. G.; Jones, D. L., A signal-dependent time-frequency representation: Optimal kernel design, IEEE Trans. Signal Process., SP-41, 4, 1589-1602 (1993) · Zbl 0775.94028 [5] Carmona, R.; Hwang, W.-L.; Torrésani, B., Practical Time-Frequency Analysis (1998), Academic Press: Academic Press San Diego, CA, Gabor and wavelet transforms with an implementation in S · Zbl 1039.42504 [6] Daubechies, I.; Maes, S., A non-linear squeezing of the continuous wavelet transform based on auditory nerve models, (Wavelets in Medicine and Biology (1996), CRC Press), Chap. 20 · Zbl 0848.92003 [7] Flandrin, P., On detection-estimation procedures in the time-frequency plane, (International Conference on Acoustics, Speech, and Signal Processing (1886)), 43.5.1-43.5.4 [8] Flandrin, P., Temps-Fréquence (1993), Hermes · Zbl 0926.94005 [9] Flandrin, P.; Escudié, B., Sur la localisation des représentations conjointes dans le plan temps-fréquence, C. R. Acad. Sci. Paris, 295, 475-478 (1982) · Zbl 0493.94002 [10] Jones, D.; Parks, T., A high reslution data-adaptive time-frequency representation, IEEE Trans. Signal Process., ASSP-38, 2127-2135 (1990) [11] Auger, P.; Flandrin, P., Improving the readibility of time-scale and time-frequency representations by using the reassignement method, IEEE Trans. Signal Process. (1995) [12] Peyrin, F.; Prost, R., A unified definition for the discrete-time, descrete-frequency and discrete-time/frequency Wigner distributions, IEEE Trans. Acoust. Speech. Signal Process., ASSP-34, 4, 858-867 (1986) [13] Stanković, L. J.; Katkovnik, V., The Wigner-Ville distribution of noisy signals with adaptive time-frequency varying window, IEEE Trans. Signal Process., 47, 4, 1099-1108 (1999) · Zbl 0978.94027 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.