By applying the method of wavelet transformation and the annual torrent runoff time series of 51 years (1951~2001) records of Longtan hydrologic station,the torrent runoff variation along the upper reaches of the Panlong River is studied. The periods of runoff and points of abrupt change at different time scales are also analyzed.
Therefore one of the most common problems encountered in gravity data studies is how to separate each anomaly. The wavelet transform operator has recently been introduced in the domain of potential fields both as a filtering and as a source-analysis tool. Here we study the ability of improving resolution gravity anomaly based on wavelet analysis and power spectrum analysis.
deeply discussed the new way of random hydrology simulation which based on the wavelet analysis; attempted to combine wavelet analysis with random analysis and establish the random model of wavelet transform;
Therefore one of the most common problems encountered in gravity data studies is how to separate each anomaly. The wavelet transform operator has recently been introduced in the domain of potential fields both as a filtering and as a source-analysis tool. Here we study the ability of improving resolution gravity anomaly based on wavelet analysis and power spectrum analysis.
Often, the Dyadic Wavelet Transform is performed and implemented with the Daubechies wavelets, the Battle-Lemarie wavelets, or the splines wavelets, whereas in continuous-time wavelet decomposition a much larger variety of mother wavelets is used.
Our work builds on a uniqueness result for reconstructing an L2 signal from irregular sampling of its wavelet transform of Grochenig and the related work of Benedetto, Heller, Mallat, and Zhong.
Unique reconstruction of band-limited signals by a Mallat-Zhong wavelet transform algorithm
Our work builds on a uniqueness result for reconstructing an L2 signal from irregular sampling of its wavelet transform of Gr?chenig and the related work of Benedetto, Heller, Mallat, and Zhong.
A Discrete Wavelet Transform without edge effects using wavelet extrapolation
In our study, we managed to carry out adaptive non-linear approximation in the field of wavelet transformation.
Applications of wavelet transformation in the nondestructive test of medium density fiberboard
Numerical experiments showed that the best among them is the method based on a three-layer neural network, the short-time Fourier transform, and the two-dimensional wavelet transformation.
Analysis of Spontaneous Electrochemical Oscillations by the Wavelet Transformation Method
A wavelet transformation is used for separation and spectral analysis of singular courses-elementary components of electrochemical oscillation recordings.
The wavelet transform is defined, and the orthogonal direct sum decomposition of function space L2(P,dμ1)) is obtained.
Based on the wavelet transform and the theory of modal acoustic emission, a new method is proposed to improve the accuracy of acoustic emission source location.
The wavelet transform is used to resolve the problem.
This paper briefly introduced the original Resonant Recognition Model (RRM), and then modified it by using the wavelet transform to acquire the Modified Resonant Recognition Model (MRRM).
The wavelet transform operator has recently been introduced into the domain fields both as a filter and as a powerful source analysis tool.