Low-pass filters and representations of the Baumslag Solitar group

We analyze representations of the Baumslag Solitar group

that admit wavelets and show how such representations can be constructed from a given low-pass filter. We describe the direct integral decomposition for some examples and derive from it a general criterion for the existence of solutions for scaling equations. As another application, we construct a Fourier transform for some Hausdorff measures.

     

"Push-the-Error" Algorithm for Nonlinear n-Term Approximation

This paper is concerned with further developing and refining the analysis of a recent algorithmic paradigm for nonlinear approximation, termed the "Push-the-Error" scheme. It is especially designed to deal with L_∞-approximation in a multilevel framework. The original version is extended considerably to cover all commonly used multiresolution frameworks. The main conceptually new result is the proof of the quasi-semi-additivity of the functional N(ε) counting the number of terms needed to achieve accuracy ε. This allows one to show that the improved scheme captures all rates of best n-term approximation.     

Optical wavelet de-noising applied in multi-span nonlinear fiber links

In this work, optical wavelet de-noising with several different types of wavelets such as db4, coif4 and dmey wavelet was applied at the end of the 40 Gbit/s multi-span intensity-modulated fiber communication systems. The results of numerical simulations carried out in different fiber links demonstrated that the optical wavelet de-noising method could remove the random amplitude fluctuation induced by the interaction of EDFA’s ASE noise and optical fiber’s dispersion and nonlinearity. The SNR and BER curves of the optical bit sequence without and with optical wavelet de-noising in dispersion compensation fiber link were plotted to show the effectiveness of the wavelet de-noising in the fiber-optic communication systems and wavelet de-noising with demy wavelet can achieve better result than with other type wavelet.     

Modification of three dimensional topography of the machined KDP crystal surface using wavelet analysis method

The wavelet analysis method has been extensively employed to analyze the surface structures and evaluate the surface roughness. In this work, however, the wavelet analysis method was introduced to decompose and reconstruct the sampled surface profile signals in the cutting direction that achieved by SPDT (single point diamond turning) operation, and the surface profile signals in tool feeding direction were reconstructed with the approximate harmonic functions directly. And moreover, the orthogonal design method, i.e. the combination design of general rotary method, was resorted to model the variations of the independent frequency and amplitude of different simulated harmonic signals in the cutting and tool feeding directions. As expected resultantly, a novel 3D surface topography modeling solution was established, which aims to predict and modify the finished KDP (potassium dihydrogen phosphate or KH₂PO₄) crystal surfaces. The validation tests were carried out finally under different cutting conditions, and the collected average surface roughness in any case was compared with the corresponding value as predicted. The results indicated the experimental data were well consistent with the predictions, and only an average relative error of 11.4% occurred in predicting the average surface roughness.     

Wavelet expansions and asymptotic behavior of distributions

We develop a distribution wavelet expansion theory for the space of highly time-frequency localized test functions over the real line S₀(R)⊂S(R) and its dual space , namely, the quotient of the space of tempered distributions modulo polynomials. We prove that the wavelet expansions of tempered distributions converge in . A characterization of boundedness and convergence in is obtained in terms of wavelet coefficients. Our results are then applied to study local and non-local asymptotic properties of Schwartz distributions via wavelet expansions. We provide Abelian and Tauberian type results relating the asymptotic behavior of tempered distributions with the asymptotics of wavelet coefficients.     

Thresholding methods to estimate copula density

This paper deals with the problem of multivariate copula density estimation. Using wavelet methods we provide two shrinkage procedures based on thresholding rules for which knowledge of the regularity of the copula density to be estimated is not necessary. These methods, said to be adaptive, have proved to be very effective when adopting the minimax and the maxiset approaches. Moreover we show that these procedures can be discriminated in the maxiset sense. We provide an estimation algorithm and evaluate its properties using simulation. Finally, we propose a real life application for financial data.     

3-D mesh sequence compression using wavelet-based multi-resolution analysis

In this paper, we present two compression methods for irregular three-dimensional (3-D) mesh sequences with constant connectivity. The proposed methods mainly use an exact integer spatial wavelet analysis (SWA) technique to efficiently decorrelate the spatial coherence of each mesh frame and also to adaptively transmit mesh frames with various spatial resolutions. To reduce the temporal redundancy, the first proposed method applies multi-order differential coding (MDC) to the temporal sequences obtained from SWA. MDC determines the optimal order of the differential coder by analyzing the variance of prediction errors. Comparing with the first order differential coding (FDC) scheme, the method can improve the compression performance. The second proposed method applies temporal wavelet analysis (TWA) to the temporal sequences. In particular, this method offers spatio-temporal multi-resolution coding. Through simulations, we prove that our methods enable efficient lossy-to-lossless compression for 3-D mesh sequences in a single frame work.     

System identification based on distribution theory and wavelet transform

A review of system identification based on distribution theory is given. By the Schwartz kernel theorem, to every continuous linear system there corresponds a unique distribution, called kernel distribution. Formulae using wavelet transform to access time--frequency information of kernel distributions are deduced. A new wavelet-based system identification method for health monitoring systems is proposed as an application of a discretized formula using stationary wavelet transform.