An adaptive wavelet method for the chemical master equation is constructed. The method is based on the representation of the solution in a sparse Haar wavelet basis, the time integration by Rothe’s method, and an iterative procedure which in each time-step selects those degrees of freedom which are essential for propagating the solution. The accuracy and efficiency of the approach is discussed,...

The wavelet periodogram is hard to smooth because of the low signal-to-noise ratio and non-stationary covariance structure. This article introduces a method for smoothing a local wavelet periodogram by applying a Haar-Fisz transform which approximately Gaussianizes and approximately stabilizes the variance of the periodogram. Consequently, smoothing the transformed periodogram can take advantag...

A Haar wavelet based numerical method for solving singularly perturbed linear time invariant system is presented in this paper. The reduced pure slow and pure fast subsystems are obtained by decoupling the singularly perturbed system and differential matrix equations are converted into algebraic Sylvester matrix equations via Haar wavelet technique. The operational matrix of integration and its...

In this paper, we present a method with a low complexity for analysing short and dynamic biomedical sequences. The method uses the Daubechies D4 wavelet in combination with similarity fitness schemes for retrieval. The method has been shown to outperform Fourier based methods in retrieving biomedical sequences of dynamic lengths, as well as the Haar wavelet.

The aim of this project is to analyze and analytical solution of different optimal control problems are difficult to obtain because they involve differential equations with single or multiple boundary conditions. In this dissertation, numerical methods using Haar Wavelet a represented to overcome this difficulty. The method reduces the differential equations into a set of line a matrix algebrai...

accurate groundwater level modeling and forecasting contribute to civil projects, land use, citys planning and water resources management. combined wavelet-artificial neural network (wann) model has been widely used in recent years to forecast hydrological and hydrogeological phenomena. this study investigates the sensitivity of the pre-processing to the wavelet type and decomposition level in ...