Reviews a significant component of the rich field of statistical multiresolution (MR) modeling
and processing. These MR methods have found application and permeated the literature of …

This article reviews the role of wavelets in statistical time–series analysis. We survey work
that emphasizes scale, such as estimation of variance, and the scale exponent of processes …

Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

This Book Identifies Problems For Which Wavelet Transform Techniques Are Well-Suited,
Shows How To Implement Wavelet Transforms Efficiently, And Explains How To Choose Or …

This paper discusses techniques for generating digital sequences of noise which simulate
processes with certain known properties or describing equations. Part I of the paper …

A joint estimator is presented for the two parameters that define the long-range dependence
phenomenon in the simplest case. The estimator is based on the coefficients of a discrete …

Fractal theory and wavelet transform analysis are two of the more significant recent
developments in mathematics that have created interest in the scientific and engineering …

Scaling phenomena have been observed in a wide range of applications. Self-similar and
long-range dependent processes are two of the most important kinds of random processes …

The presence of scaling behavior in telecommunications traffic is striking not only in its
ubiquity, appearing in almost every kind of packet data, but also in the wide range of scales …

It is demonstrated that 1/f fractal processes are, in a broad sense, optimally represented in
terms of orthonormal wavelet bases. Specifically, via a useful frequency-domain …