Motivation • Seasonal long memory is gaining attention as a time series model in econometrics and the physical sciences. { Arteche and Robinson (2000) proposed log-periodogram regression and Gaussian semi-parametric estimation for seasonal long-memory processes. • The discrete wavelet transform (DWT) is a useful alternative to the discrete Fourier transform for the analysis and synthesis of lon...

This paper presents a method for prediction short-term power demand of a vehicular power system. The forecasting of power demand is presented using wavelet decomposition and artificial neural network, a hybrid model which absorbs some merits of wavelet transform and neural network. The power demand time series is first decomposed into a certain number of levels with discreet wavelet transform a...

There are a lot of wavelet-based approaches in digital image watermarking literature. In these approaches, the main issue is selection method of wavelet sub-bands’ coefficients and embedding algorithm. In this approach, an entropy-based method is proposed for non-blind watermarking of still gray level images using discrete wavelet transform. In our approach, we have also used the Discrete Wavel...

The 2-band discrete wavelet transform (DWT) provides an octave-band analysis in the frequency domain, but this might not be ‘optimal’ for a given signal. The discrete wavelet packet transform (DWPT) provides a dictionary of bases over which one can search for an optimal representation (without constraining the analysis to an octave-band one) for the signal at hand. However, it is well known tha...

Image fusion is processes of combining complementary information from a set of input images. The resultant fused image give large and reliable information. In this paper we study about Discrete wavelet and Discrete Multiwavelet and there use in image fusion. Discrete wavelet transform (DWT) technique is used for multi Resolution fusion. Multi Resolution fusion uses wavelet transform at multi sc...

Discrete wavelet transforms (DWTs) are mathematical tools that are useful for analyzing geophysical time series. The basic idea is to transform a time series into coefficients describing how the series varies over particular scales. One version of the DWT is the maximal overlap DWT (MODWT). The MODWT leads to two basic decompositions. The first is a scale-based analysis of variance known as the...

Recently, research on two distinct types of wavelet frames have emerged, each with its own characteristics. The dual-tree discrete wavelet transform (DWT) [1] is based on the concatenation of two wavelet bases, where the two wavelets are designed to form a Hilbert transform pair, Ãg(t) = HfÃh(t)g [4]. A second type of wavelet frame is based on a single scaling function and two distinct wavelets...

In this paper, a new face recognition system based on Wavelet transform (HWT) and Principal Component Analysis (PCA) is presented. The image face is preprocessed and detected. The Haar wavelet is used to form the coefficient matrix for the detected face. The image feature vector is obtained by computing PCA for the coefficient matrix of DWT. A comparison between the proposed recognition system ...

In this correspondence, an image resolution enhancement technique based on interpolation of the high frequency subband images obtained by discrete wavelet transform (DWT), stationary wavelet transform (SWT) and the input image has been proposed. The image quality has been enhanced by incorporating stationary wavelet transform (SWT). DWT decomposes an input image into four subbands. Out of these...

In this paper, a new method for handwritten signature identification based on rotated complex wavelet filters is proposed. We have proposed to use the rotated complex wavelet filters (RCWF) and dual tree complex wavelet transform(DTCWT) together to derive signature feature extraction, which captures information in twelve different directions. In identification phase, Canberra distance measure i...