The paper proposes a wavelet-based forecasting method for time series. We used the multi-resolution decomposition of the signal implemented using trous wavelet transform. We combined the Stationary Wavelet Transform (SWT) with four prediction methodologies: Artificial Neural Networks, ARIMA, Linear regression and Random walk. These techniques were applied to two types of real data series: WiMAX...

Wavelet-based image compression provides substantial improvements in picture quality at higher compression ratios. Haar wavelet transform based compression is one of the methods that can be applied for compressing images. An ideal image compression system must yield good quality compressed images with good compression ratio, while maintaining minimal time cost. With Wavelet transform based comp...

A wavelet analysis, in the context of multiresolution. is performed to study the distribution of matter in the universe at extragalactic scales. Specifically, a threedimensional Haar system is used to extract statistical properties of large-scale structure. Despite the simplicity of the wavelet form, the method is effective for identifying general properties of gravitational clustering phenomen...

This article introduces a new method for the estimation of the intensity of an inhomogeneous one-dimensional Poisson process. The Haar-Fisz transformation transforms a vector of binned Poisson counts to approximate normality with variance one. Hence we can use any suitable Gaussian wavelet shrinkage method to estimate the Poisson intensity. Since the Haar-Fisz operator does not commute with the...

This work shows a robust Watermarking method to be introduced in audio files. The new in this method is the use of the Wavelet Haar Transform in combination with Patcwork algorithm in the frequency domain. This combination makes the Watermarking robust against compression, filtering and resampling. We use MATLAB to implement the tests of audio files.

In this paper, we study the numerical method for solving second-order fuzzy differential equations using single term Haar wavelet series (STHWS). And, we present two examples with initial condition [16] having two different solutions to illustrate the efficiency of the proposed method under STHWS. Error graphs are presented to highlight the efficiency of the STHWS.

Over the last years, wavelet theory has been used with great success in a wide range of applications as signal denoising and image compression. An ideal image compression system must yield high-quality compressed image with high compression ratio. This paper attempts to find the most useful wavelet function to compress an image among the existing members of wavelet families. Our idea is that a ...

In this article, a novel and efficient collocation method based on Fibonacci wavelets is proposed for the numerical solution of non-linear Hunter–Saxton equation. Firstly, operational matrices integration associated with are constructed by following strategy Chen Hsiao. The merged used to convert given problem into system algebraic equations that can be solved any classical method, such as Newt...

In this paper Adomian's Decomposition Method (ADM) is employed to solve observer design in generalized state space or singular system of transistor circuits. From the example, the solution of singular system of transistor circuits shows that the ADM is more simple and easy to use than Haar Wavelet and Single Term Walsh Series (STWS) method.

In this paper, a generalized method as Single term Haar wavelet series (STHWS) for solving linear singular systems is discussed. This new approach provides a better effectiveness to find discrete solutions of different order singular systems for any length of time t. This is a direct method and can be easily implemented in a digital computer.