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Measurement and modeling of the temporal dependence in packet loss
, 1999
"... Abstract — Understanding and modelling packet loss in the Internet is especially relevant for the design and analysis of delaysensitive multimedia applications. In this paper, we present analysis of ¢¡¤ £ hours of endtoend unicast and multicast packet loss measurement. From these we selected ¥§ ¦ ..."
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Cited by 220 (12 self)
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Abstract — Understanding and modelling packet loss in the Internet is especially relevant for the design and analysis of delaysensitive multimedia applications. In this paper, we present analysis of ¢¡¤ £ hours of endtoend unicast and multicast packet loss measurement. From these we selected ¥§ ¦ hours of stationary traces for further analysis. We consider the dependence as seen in the autocorrelation function of the original loss data as well as the dependence between good run lengths and loss run lengths. The correlation timescale is found to be ¢¨¤¨¤¨§©� � or less. We evaluate the accuracy of three models of increasing complexity: the Bernoulli model, the 2state Markov chain model and � theth order Markov chain model. Out of � £ the trace segments considered, the Bernoulli model was found to be accurate for ¥ segments, the 2state model was found to be accurate for ¢ ¨ segments. A Markov chain model of order ¡ or greater was found to be necessary to accurately model the rest of the segments. For the case of adaptive applications which track loss, we address two issues of online loss estimation: the required memory size and whether to use exponential smoothing or a sliding window average to estimate average loss rate. We find that a large memory size is necessary and that the sliding window average provides a more accurate estimate for the same effective memory size. I.
Hidden Markov Modeling of Flat Fading Channels
 IEEE Journal on Selected Areas in Communications
, 1998
"... Abstract — Hidden Markov models (HMM’s) are a powerful tool for modeling stochastic random processes. They are general enough to model with high accuracy a large variety of processes and are relatively simple allowing us to compute analytically many important parameters of the process which are very ..."
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Cited by 45 (0 self)
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Abstract — Hidden Markov models (HMM’s) are a powerful tool for modeling stochastic random processes. They are general enough to model with high accuracy a large variety of processes and are relatively simple allowing us to compute analytically many important parameters of the process which are very difficult to calculate for other models (such as complex Gaussian processes). Another advantage of using HMM’s is the existence of powerful algorithms for fitting them to experimental data and approximating other processes. In this paper, we demonstrate that communication channel fading can be accurately modeled by HMM’s, and we find closedform solutions for the probability distribution of fade duration and the number of level crossings. Index Terms — Fading channels, hidden Markov models, parameter estimation.
Physiological time series analysis: what does regularity quantify
 Am J Physiol
, 1994
"... cal timeseries analysis: what does regularity quantify? Am. J. ..."
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Cited by 20 (0 self)
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cal timeseries analysis: what does regularity quantify? Am. J.
The Caenorhabditis elegans gene unc89, required for muscle Mline assembly, encodes a giant modular protein composed of Ig and signal transduction domains
 J. Cell. Biol
, 1996
"... Abstract. Mutations in the Caenorhabditis elegans gene unc89 result in nematodes having disorganized muscle structure in which thick filaments are not organized into Abands, and there are no Mlines (Waterston, R.H., J.N. Thomson, and S. Brenner. 1980. Dev. Biol. 77:271302). Beginning with a part ..."
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Cited by 19 (7 self)
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Abstract. Mutations in the Caenorhabditis elegans gene unc89 result in nematodes having disorganized muscle structure in which thick filaments are not organized into Abands, and there are no Mlines (Waterston, R.H., J.N. Thomson, and S. Brenner. 1980. Dev. Biol. 77:271302). Beginning with a partial cDNA from the C. elegans sequencing project, we have cloned and sequenced the unc89 gene. An unc89 allele, st515, was found to contain an 84bp deletion and a 10bp duplication, resulting in an inframe stop codon within predicted unc89 coding sequence. Analysis of the complete coding sequence for unc89 predicts a novel 6,632amino acid potypeptide consisting of sequence motifs which have been implicated in proteinprotein interactions. UNC89 begins with 67 residues of unique sequence, SH3, dbl/CDC24, and PH domains, 7 immunoglobulin (Ig) domains, a putative KSPcontaining multiphosphorylation domain, and ends with 46 Ig domains. A polyclonal antiserum raised to a portion of unc89 encoded sequence reacts to a twitchinsized polypeptide from wild type, but truncated polypeptides from st515 and from the amber allele e2338. By immunofluorescent microscopy, this antiserum localizes to the middle of Abands, consistent with UNC89 being a structural component of the Mline. Previous studies indicate that myofilament lattice assembly begins with positional cues laid down in the basement membrane
Markov Types and Minimax Redundancy for Markov Sources
 IEEE Trans. Information Theory
, 2003
"... Redundancy of universal codes for a class of sources determines by how much the actual code length exceeds the optimal code length. In the minimax scenario one designs the best code for the worst source within the class. Such minimax redundancy comes in two flavors: either on average or for individu ..."
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Cited by 18 (10 self)
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Redundancy of universal codes for a class of sources determines by how much the actual code length exceeds the optimal code length. In the minimax scenario one designs the best code for the worst source within the class. Such minimax redundancy comes in two flavors: either on average or for individual sequences. The latter is also known as the maximal or the worst case minimax redundancy. We study the maximal minimax redundancy of universal block codes for Markovian sources of any order. We prove that the maximal minimax redundancy for Markov sources of order r is asymptotically equal to 1) log 2 n + log 2 A (ln ln m 1/(m1) )/ ln m + o(1), where n is the length of a source sequence, m is the size of the alphabet and A m is an explicit constant (e.g., we find that for a binary alphabet m = 2 and Markov of order r = 1 the constant 14.655449504 where G is the Catalan number). Unlike previous attempts, we view the redundancy problem as an asymptotic evaluation of certain sums over a set of matrices representing Markov types. The enumeration of Markov types is accomplished by reducing it to counting Eulerian paths in a multigraph. In particular, we propose an asymptotic formula for the number of strings of a given Markov type. All of these findings are obtained by analytic and combinatorial tools of analysis of algorithms. Index terms: Minimax redundancy, Markov sources, Markov types, Eulerian paths, multidimensional generating functions, analytic information theory. # A preliminary version of this paper was presented at Colloquium on Mathematics and Computer Science: Algorithms, Trees, Combinatorics and Probabilities, Versailles, 2002.
A measurementbased model for dynamic spectrum access
 in Proc. IEEE Conference on Military Communications (MILCOM
, 2006
"... Abstract — In this paper we consider dynamically sharing the spectrum in the timedomain by exploiting whitespace between the bursty transmissions of a set of users, represented by an 802.11b based wireless LAN (WLAN). Realizing that exploiting the underutilization of the channel requires a good mo ..."
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Cited by 15 (6 self)
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Abstract — In this paper we consider dynamically sharing the spectrum in the timedomain by exploiting whitespace between the bursty transmissions of a set of users, represented by an 802.11b based wireless LAN (WLAN). Realizing that exploiting the underutilization of the channel requires a good model of the these users ’ medium access, we propose a continuoustime semiMarkov model that captures the WLAN’s behavior yet remains tractable enough to be used for deriving optimal control strategies within a decisiontheoretic framework. Our model is based on actual measurements in the 2.4 GHz ISM band using a vector signal analyzer to collect complex baseband data. We explore two different sensing strategies to identify spectrum opportunities depending on whether the primary user’s transmission scheme is known. The collected data is used to statistically characterize the idle and busy periods of the channel. Furthermore, we show that a continuoustime semiMarkov model is able to capture the data with good accuracy. The KolmogorovSmirnov test is used to validate the model and to assess the model’s goodnessoffit quantitatively. A conclusion summarizes the main results of the paper. I.
Statistical Techniques for Language Recognition: An Introduction and Guide for Cryptanalysts
 Cryptologia
, 1993
"... We explain how to apply statistical techniques to solve several languagerecognition problems that arise in cryptanalysis and other domains. Language recognition is important in cryptanalysis because, among other applications, an exhaustive key search of any cryptosystem from ciphertext alone requir ..."
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Cited by 12 (2 self)
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We explain how to apply statistical techniques to solve several languagerecognition problems that arise in cryptanalysis and other domains. Language recognition is important in cryptanalysis because, among other applications, an exhaustive key search of any cryptosystem from ciphertext alone requires a test that recognizes valid plaintext. Written for cryptanalysts, this guide should also be helpful to others as an introduction to statistical inference on Markov chains. Modeling language as a finite stationary Markov process, we adapt a statistical model of pattern recognition to language recognition. Within this framework we consider four welldefined languagerecognition problems: 1) recognizing a known language, 2) distinguishing a known language from uniform noise, 3) distinguishing unknown 0thorder noise from unknown 1storder language, and 4) detecting nonuniform unknown language. For the second problem we give a most powerful test based on the NeymanPearson Lemma. For the oth...
Impulse Generation With Appropriate Amplitude, Length, InterArrival, and Spectral Characteristics
 IEEE Journal on Selected Areas in Communications
, 2002
"... This paper proposes a suitable method for simulating impulses with appropriate amplitude, spectral, and interarrival characteristics. The statistics used to develop the parameters of this model are based on statistics derived from observations of impulse noise on the telephone networks of British T ..."
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Cited by 11 (1 self)
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This paper proposes a suitable method for simulating impulses with appropriate amplitude, spectral, and interarrival characteristics. The statistics used to develop the parameters of this model are based on statistics derived from observations of impulse noise on the telephone networks of British Telecom (BT) and Deutsche Telekom (DT). This paper initially reviews the former DT approach to impulse noise generation for testing digital subscriber line systems, so called xDSL systems. Some problems are highlighted and an alternative technique is suggested that is capable of generating impulses with both appropriate amplitude and spectral characteristics.
Testing composite hypotheses about discretevalued stationary processes
 In ITW : 291– 295
"... processes ..."
Web Interaction and the Navigation Problem in Hypertext written for Encyclopedia of Microcomputers
, 2001
"... The web has become a ubiquitous tool, used in daytoday work, to find information and conduct business, and it is revolutionising the role and availability of information. One of the problems encountered in web interaction, which is still unsolved, is the navigation problem, whereby users can &q ..."
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Cited by 11 (8 self)
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The web has become a ubiquitous tool, used in daytoday work, to find information and conduct business, and it is revolutionising the role and availability of information. One of the problems encountered in web interaction, which is still unsolved, is the navigation problem, whereby users can "get lost in hyperspace", meaning that when following a sequence of links, i.e. a trail of information, users tend to become disoriented in terms of the goal of their original query and the relevance to the query of the information they are currently browsing. Herein we build statistical foundations for tackling the navigation problem based on a formal model of the web in terms of a probabilistic automaton, which can also be viewed as a finite ergodic Markov chain. In our model of the web the probabilities attached to state transitions have two interpretations, namely, they can denote the proportion of times a user followed a link, and alternatively they can denote the expected utility of following a link. Using this approach we have developed two techniques for constructing a web view based on the two interpretations of the probabilities of links, where a web view is a collection of relevant trails. The first method we describe is concerned with finding frequent user behaviour patterns. A collection of trails is taken as input and an ergodic Markov chain is produced as output with the probabilities of transitions corresponding to the frequency the user traversed the associated links. The second method we describe is a reinforcement learning algorithm that attaches higher probabilities to links whose expected trail relevance is higher. The user's home page and a query are taken as input and an ergodic Markov chain is produced as output with the probabilities of...