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A multifractal wavelet model with application to network traffic

R.H. Riedi, M.S. Crouse, V.J. Ribeiro, R.G. Baraniuk
1999 IEEE Transactions on Information Theory  
Using the Haar wavelet transform and a special multiplicative structure on the wavelet and scaling coefficients to ensure positive results, the model provides a rapid O(N ) cascade algorithm for synthesizing  ...  Although for illustrative purposes we focus on applications in network traffic modeling, the multifractal wavelet model could be useful in a number of other areas involving positive data, including image  ...  A Multifractal Wavelet Model with Application to Network Traffic I. INTRODUCTION A.  ... 
doi:10.1109/18.761337 fatcat:worhp2wlpvc4doxmc4z55nfw5u

Modeling heterogeneous network traffic in wavelet domain

Sheng Ma, Chuanyi Ji
2001 IEEE/ACM Transactions on Networking  
Heterogeneous network traffic possesses diverse statistical properties which include complex temporal correlation and non-Gaussian distributions.  ...  This assesses the performance of the independent wavelet model, and the use of which for analysis.  ...  Vastola for helpful discussions, and the anonymous reviewers and the Associate Editor for helpful comments.  ... 
doi:10.1109/90.958331 fatcat:6svv7vvapjdq3e74r46xhn3jgm

Empirical Testing Of The Infinite Source Poisson Data Traffic Model

C. A. Guerin, H. Nyberg, O. Perrin, S. Resnick, H. Rootzén, C. Stărică
2003 Stochastic Models  
We survey the self-similarity properties of various descriptor processes in this model and then present analyses of four data sets which show that certain features of the model are consistent with the  ...  We survey some features of this model in cases where transmission length distributions have (a) tails so heavy that means are infinite, (b) heavy tails with finite mean and infinite variance and (c) finite  ...  Istas for useful conversations and help with details and references.  ... 
doi:10.1081/stm-120020386 fatcat:pprbcgdoerf6xogdgswxpi3ag4

Wavelet analysis of long-range-dependent traffic

P. Abry, D. Veitch
1998 IEEE Transactions on Information Theory  
A wavelet-based tool for the analysis of long-range dependence and a related semi-parametric estimator of the Hurst parameter is introduced.  ...  Statistical, computational, and numerical comparisons are made against traditional estimators including that of Whittle.  ...  Willinger for constructive remarks on this work during Les Houches spring school on long-range dependence, May'96.  ... 
doi:10.1109/18.650984 fatcat:e7vk6pgb5nhv7cnobisor4vxym

A Novel Method for Control Performance Assessment with Fractional Order Signal Processing and Its Application to Semiconductor Manufacturing

Kai Liu, YangQuan Chen, Paweł Domański, Xi Zhang
2018 Algorithms  
The on-line control loop performance monitoring with non-Gaussian statistical and fractal measure has been proposed in [6] .  ...  At last, non-Gaussian statistical properties, multifractal properties and Hurst exponents of the process control variables are derived and compared with different sets of tuning parameters.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/a11070090 fatcat:d737xtancvbq3asiw6xc224orm

Ch. 3. Locally self-similar processes and their wavelet analysis [chapter]

Joseph E. Cavanaugh, Yazhen Wang, J. Wade Davis
2003 Handbook of Statistics  
a maximum likelihood estimator based on the periodogram.  ...  Our reliance on wavelets is further motivated by the computational efficiency of the discrete wavelet transformation as well as the successful application of wavelets in problems dealing with both non-stationarity  ...  In our proofs, we use K to denote constants that may vary in specification from one usage to the next. In the proof of Theorem 6, these constants may depend on t but not on the scales a.  ... 
doi:10.1016/s0169-7161(03)21005-1 fatcat:j2am2t27vvgb7cawxj5wf35ti4

Quantification of Long-Range Persistence in Geophysical Time Series: Conventional and Benchmark-Based Improvement Techniques

Annette Witt, Bruce D. Malamud
2013 Surveys in geophysics  
on networks such as internet traffic (Leland et al. 1994; Willinger et al. 1997).  ...  639 axes the variance grows (the fluctuations are non-stationary), but on loglog axes, they are approximately stationary.  ... 
doi:10.1007/s10712-012-9217-8 fatcat:2nr4doiinvdv5j2tagp6pejkd4

Phase-modulated resonances modeled as self-similar processes with application to turbulent sounds

A.G. Dimakis, P. Maragos
2005 IEEE Transactions on Signal Processing  
As a special case, this random phase model includes the class of random fractal signals known as fractional Brownian motion.  ...  The main motivation of our work stems from previous experimental and theoretical evidence that speech resonances in fricative sounds can be modeled phenomenologically as AM-FM signals with randomly varying  ...  Specifically, a variety of methods have been proposed, and they include, among others, least squares estimation of the slope of log-axes plots of sample periodograms, methods based on wavelets, aggregated  ... 
doi:10.1109/tsp.2005.857010 fatcat:3dbbpawldfbh3fksbiuoatvpuy

Fractals in the nervous system: conceptual implications for theoretical neuroscience

Gerhard Werner
2010 Frontiers in Physiology  
This essay is presented with two principal objectives in mind: first, to document the prevalence of fractals at all levels of the nervous system, giving credence to the notion of their functional relevance  ...  The final Section consists of general reflections on the implications of the reviewed data, and identifies what appear to be issues of fundamental importance for future research in the rapidly evolving  ...  Physical process models to account for fractal heavy-tailed distributions of traffic pattern of (information) packages in local area networks (LANs) are based on renewal reward processes, originally applied  ... 
doi:10.3389/fphys.2010.00015 pmid:21423358 pmcid:PMC3059969 fatcat:qjhzo4ioarg35crh3eblkxfyiq

Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience [article]

Gerhard Werner
2010 arXiv   pre-print
This essay is presented with two principal objectives in mind: first, to document the prevalence of fractals at all levels of the nervous system, giving credence to the notion of their functional relevance  ...  The final Section consists of general reflections on the implications of the reviewed data, and identifies what appear to be issues of fundamental importance for future research in the rapidly evolving  ...  non-stationary and non-differentiable time functions (see Section 2).  ... 
arXiv:0910.2741v2 fatcat:nj6zeigotrdnrkaoivgcjxcuke

Inertia and memory in ambiguous visual perception

J. B. Gao, V. A. Billock, I. Merk, W. W. Tung, K. D. White, J. G. Harris, V. P. Roychowdhury
2006 Cognitive Processing  
encephalography, simultaneous recordings of groups of neurons in many areas of the brain, and concepts from statistical mechanics and nonlinear dynamics theory.  ...  The long memory feature contrasts sharply with the traditional satiation models of multistability, where the memory is not incorporated, as well as with recently published models of multistability and  ...  In order to estimate the Hurst parameter, we calculated var(X (m) ) for various m, and plotted var(X (m) ) versus m under log-log transformation as Fig. 5a .  ... 
doi:10.1007/s10339-006-0030-5 pmid:16683173 fatcat:rt4j5zobk5g6xd7xqfmwvadope

A Novel Rebroadcast Technique for Reducing Routing Overhead In Mobile Ad Hoc Networks

Vinayak T Patil
2013 IOSR Journal of Computer Engineering  
One of the fundamental challenges of MANETs is the design of dynamic routing protocols with good performance and less overhead.  ...  In mobile ad hoc networks (MANETs), the network topology changes frequently and unpredictably due to the arbitrary mobility of nodes.  ...  Ashish Kumar Srivastava and co-guide Prof. Sitendra Tamrakar in writing this paper and giving the valuable suggestion.  ... 
doi:10.9790/0661-1260109 fatcat:jundvgfvpjcdpmtloz2z2w6ige

Multiresolution Markov models for signal and image processing

A.S. Willsky
2002 Proceedings of the IEEE  
We discuss the construction of MR models on trees and show how questions that arise in this context make contact with wavelets, state space modeling of time series, system and parameter identification,  ...  This paper reviews a significant component of the rich field of statistical multiresolution (MR) modeling and processing.  ...  Basseville, not only for hosting his 1988 sabbatical but also for suggesting that they use that time to see if they could make sense of multiresolution methods and, in particular, wavelets, from a statistical  ... 
doi:10.1109/jproc.2002.800717 fatcat:lbs3ddxxpff4ndiutddn4ziq6m

DWT Based Image Compression for Health Systems

Ibrahim Abdulai Sawaneh
2018 Journal of advanced research in Medical and Health science  
Therefore this report presents data compression implementation for healthcare systems using a proposed scheme of discrete wavelet transform (DWT), Fourier transform (FT) and Fast Fourier transform with  ...  Our experimental implementation shows that using Haar wavelet with parametric determination of MSE and PSNR solve our aims.  ...  Acknowledgement The report would not have been feasible without the divine direction of Allah. I  ... 
doi:10.53555/nnmhs.v4i9.603 fatcat:tqch52kvxfhcrbex2gfcq2qs6a

Multifractal analysis of financial markets [article]

Zhi-Qiang Jiang , Didier Sornette
2018 arXiv   pre-print
Inspired by its striking analogy with hydrodynamic turbulence, from which the idea of multifractality originated, multifractal analysis of financial markets has bloomed, forming one of the main directions  ...  We survey the cumulating evidence for the presence of multifractality in financial time series in different markets and at different time periods and discuss the sources of multifractality.  ...  The length of the non-overlapping segment on each time scale is computed through the Hilbert transform and each of the extracted fluctuations is partitioned into non-overlapping segments with identical  ... 
arXiv:1805.04750v1 fatcat:dtwjemhhxjcxhibzthx6rrmdom
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