The wavelet transform, time-frequency localization and signal analysis
By Ingrid Daubechies. 1990
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
Citations in the corpus
- Parallel Wavegan: A Fast Waveform Generation Model Based on Generative Adversarial Networks with Multi-Resolution Spectrogram (2019, methodology): “…multi-resolution STFT auxiliary loss ( L aux ) is represented as follows: In the STFT-based time-frequency representation of signals, there is a trade-off between time and frequency resolution; e.g., increasing window size gives higher frequency resolution while reducing temporal resolution [24].”
- Gabor Frames in Finite Dimensions (2013, background): “In the second half of the 20th century, the suggestion of Gabor, and in general the interplay of information density in time and in frequency, was studied extensively; see, for example, [23, 24, 32, 37, 59, 60, 61, 85].”
- Error Minimized Extreme Learning Machine With Growth of Hidden Nodes and Incremental Learning (2009, background): “Such computational hidden nodes include additive/radial basis function (RBF) hidden nodes, multiplicative nodes, fuzzy rules [11], fully complex nodes [12], [13], hinging functions [14], high-order nodes [15], ridge polynomials [16], wavelets [17], [18], Fourier series [19], etc.”
- Analyzing information flow in brain networks with nonparametric Granger causality (2008, background): “The wavelet transform provides time-frequency representation of a signal and is useful to analyze time-varying (nonstationary) processes (Daubechies, 1990; 1992; Percival and Walden, 2000).”
- Time-Frequency Analysis of Sj\"ostrand's Class (2004, background): “aves like an orthonormal expansion (with the exception that the coefficients are not unique). The existence and construction of Gabor frames for separable lattices Λ = αZd× βZd) is well understood (see [13,21,30,45]) and we may take the existence of Gabor frames with suitable g for granted. The expans”