Article history: Received 9 September 2012 Received in revised form 19 December 2013 Accepted 29 December 2013 Available online xxxx Communicated by Peter Oswald

We present a comparative study between a complex Wavelet Coeecient Shrinkage (WCS) lter and several standard speckle lters that are widely used in the radar imaging community (Lee, Kuan, Frost, Geometric, Kalman, Gamma, etc.). The WCS lter is based on the use of Symmetric Daubechies (SD) wavelets which share the same properties as the real Daubechies wavelets but with an additional symmetry pro...

At the 60 GHz band a massive amount of spectral space (5 GHz) has been allocated unlicensed worldwide for dense wireless local communications. OFDM has gained much popularity in the field of wireless communication because of its ability to transfer the data at higher rate, high bandwidth efficiency and robustness to multipath and delay.The BER performance of conventional FFT-OFDM system is comp...

Explicit solutions are given for the rational function P (z) for two classes of IIR orthogonal two-band wavelet bases, for which the scaling filter is maximally flat. P (z) denotes the rational transfer function H(z)H(1=z), where H(z) is the (lowpass) scaling filter. The first is the class of solutions that are intermediate between the Daubechies and the Butterworth wavelets. It is found that t...

This paper studies long-memory properties of stock prices in PIIGS economies (Portugal, Ireland, Italy, Greece and Spain) and measures the evolution of their long-memory phenomena over time. We use the Hurst exponent as a measure of long-range dependence in stock prices. We apply wavelet analysis (based on Haar, Daubechies-4, Daubechies12 and Daubechies-20 wavelets) for computation of Hurst exp...

Wavelet decomposition in signal processing has been widely used the literature. The popularity of machine learning (ML) algorithms is increasing day by agriculture, from irrigation scheduling and yield prediction to price prediction. It quite interesting study wavelet-based stochastic ML models appropriately choose most suitable wavelet filters predict agricultural commodity prices. In present ...

A large body of nonparametric statistical literature is devoted to density estimation. Overviews are given in Silverman (1986) and Izenman (1991). This paper addresses the problem of univariate density estimation in a novel way. Our approach falls in the class of so called projection estimators, introduced by Cencov (1962). The orthonor-mal basis used is a basis of compactly supported wavelets ...