Blind channel estimation and data detection using hidden Markov models theory

In this correspondence, we propose applying the hiddenMarkov models (HMM) theory to the problem of blind channel estimationand data detection. The Baum–Welch (BW) algorithm, which is able toestimate all the parameters of the model, is enriched by introducingsome linear constraints emerging from a linear FIR hypothesis on thechannel. Additionally, a version of the algorithm that is suitable for timevaryingchannels is also presented. Performance is analyzed in a GSMenvironment using standard test channels and is found to be close to thatobtained with a nonblind receiver.

Motion estimation using higher-order statistics

The objective of this paper is to introduce a fourth-order cost function of the displaced frame difference (DFD) capable of estimatingmotion even for small regions or blocks. Using higher than second-orderstatistics is appropriate in case the image sequence is severely corruptedby additive Gaussian noise. Some results are presented and compared to those obtained from the mean kurtosis and the mean square error of the DFD.

Average performance analysis of circular and hyperbolic geolocation

A comparative performance analysis of four geolocation methods in terms of their theoretical root mean square positioning errors is provided. Comparison is established in two different ways: strict and average. In the strict type, methods are examined for a particular geometric configuration of base stations(BSs) with respect to mobile position, which determines a givennoise profile affecting the respective time-of-arrival (TOA) or timedifference-of-arrival (TDOA) estimates. In the average type, methodsare evaluated in terms of the expected covariance matrix ofthe position error over an ensemble of random geometries, so thatcomparison is geometry independent. Exact semianalytical equationsand associated lower bounds (depending solely on the noiseprofile) are obtained for the average covariance matrix of the positionerror in terms of the so-called information matrix specific toeach geolocation method. Statistical channel models inferred fromfield trials are used to define realistic prior probabilities for therandom geometries. A final evaluation provides extensive resultsrelating the expected position error to channel model parametersand the number of base stations.

Second-order parameter estimation

This work provides a general framework for the design of second-order blind estimators without adopting anyapproximation about the observation statistics or the a prioridistribution of the parameters. The proposed solution is obtainedminimizing the estimator variance subject to some constraints onthe estimator bias. The resulting optimal estimator is found todepend on the observation fourth-order moments that can be calculatedanalytically from the known signal model. Unfortunately,in most cases, the performance of this estimator is severely limitedby the residual bias inherent to nonlinear estimation problems.To overcome this limitation, the second-order minimum varianceunbiased estimator is deduced from the general solution by assumingaccurate prior information on the vector of parameters.This small-error approximation is adopted to design iterativeestimators or trackers. It is shown that the associated varianceconstitutes the lower bound for the variance of any unbiasedestimator based on the sample covariance matrix.The paper formulation is then applied to track the angle-of-arrival(AoA) of multiple digitally-modulated sources by means ofa uniform linear array. The optimal second-order tracker is comparedwith the classical maximum likelihood (ML) blind methodsthat are shown to be quadratic in the observed data as well. Simulationshave confirmed that the discrete nature of the transmittedsymbols can be exploited to improve considerably the discriminationof near sources in medium-to-high SNR scenarios.

NDA waveform estimation in the low-SNR regime

This correspondence addresses the problem of nondata-aidedwaveform estimation for digital communications. Based on the unconditionalmaximum likelihood criterion, the main contribution of this correspondenceis the derivation of a closed-form solution to the waveform estimationproblem in the low signal-to-noise ratio regime. The proposed estimationmethod is based on the second-order statistics of the received signaland a clear link is established between maximum likelihood estimation andcorrelation matching techniques. Compression with the signal-subspace isalso proposed to improve the robustness against the noise and to mitigatethe impact of abnormals or outliers.

Maximum likelihood estimation of position in GNSS

In this letter, we obtain the Maximum LikelihoodEstimator of position in the framework of Global NavigationSatellite Systems. This theoretical result is the basis of a completelydifferent approach to the positioning problem, in contrastto the conventional two-steps position estimation, consistingof estimating the synchronization parameters of the in-viewsatellites and then performing a position estimation with thatinformation. To the authors’ knowledge, this is a novel approachwhich copes with signal fading and it mitigates multipath andjamming interferences. Besides, the concept of Position–basedSynchronization is introduced, which states that synchronizationparameters can be recovered from a user position estimation. Weprovide computer simulation results showing the robustness ofthe proposed approach in fading multipath channels. The RootMean Square Error performance of the proposed algorithm iscompared to those achieved with state-of-the-art synchronizationtechniques. A Sequential Monte–Carlo based method is used todeal with the multivariate optimization problem resulting fromthe ML solution in an iterative way.

Monte Carlo Methods in Parameter Estimation of Nonlinear Models

Yksi keskeisimmistä tehtävistä matemaattisten mallien tilastollisessa analyysissä on mallien tuntemattomien parametrien estimointi. Tässä diplomityössä ollaan kiinnostuneita tuntemattomien parametrien jakaumista ja niiden muodostamiseen sopivista numeerisista menetelmistä, etenkin tapauksissa, joissa malli on epälineaarinen parametrien suhteen. Erilaisten numeeristen menetelmien osalta pääpaino on Markovin ketju Monte Carlo -menetelmissä (MCMC). Nämä laskentaintensiiviset menetelmät ovat viime aikoina kasvattaneet suosiotaan lähinnä kasvaneen laskentatehon vuoksi. Sekä Markovin ketjujen että Monte Carlo -simuloinnin teoriaa on esitelty työssä siinä määrin, että menetelmien toimivuus saadaan perusteltua. Viime aikoina kehitetyistä menetelmistä tarkastellaan etenkin adaptiivisia MCMC menetelmiä. Työn lähestymistapa on käytännönläheinen ja erilaisia MCMC -menetelmien toteutukseen liittyviä asioita korostetaan. Työn empiirisessä osuudessa tarkastellaan viiden esimerkkimallin tuntemattomien parametrien jakaumaa käyttäen hyväksi teoriaosassa esitettyjä menetelmiä. Mallit kuvaavat kemiallisia reaktioita ja kuvataan tavallisina differentiaaliyhtälöryhminä. Mallit on kerätty kemisteiltä Lappeenrannan teknillisestä yliopistosta ja Åbo Akademista, Turusta.

Nappe geometry in the Western Swiss Alps

Detailed geological mapping during the last 20 years in the Western Swiss Alps has shown clearly that most of the lower basement nappes are fold nappes possessing normal and inverted limbs. Moreover their cores are made of strongly deformed gneisses indicating that important ductile strain took place during the formation of the fold nappes. It is therefore probably wrong to imagine deep basement nappes as rigid slices as often actually claimed, especially when interpreting seismic profiles. True `brittle type' thrust nappes involving basement rocks only occur in the internal and upper parts of the belt. Cover nappes, on the contrary, are in most parts of the Alpine belt thrust sheets following more or less the rules of thin-skinned tectonics. Many basement fold nappes lost part of their sedimentary cover during or just before their formation, by decollement along ductile horizons. The result is that many cover thrust nappes in the external part of the Alps are directly related to their original basement fold nappes.

Estimation des crues extrêmes dans les Alpes suisses a l'aide d'un modèle hydrologique distribué

Les modèles hydrologiques développés pour les pluies extrêmes de type PMP sont difficiles à paramétrer en raison du manque de données disponibles pour ces évènements et de la complexité du terrain. Cet article présente les processus et les résultats de l'ajustement des paramètres pour un modèle hydrologique distribué. Ce modèle à une échelle fine a été développé pour l'estimation des crues maximales probables dans le cas d'une PMP. Le calcul effectué pour deux bassins versants test suisses et pour deux épisodes d'orages d'été concerne l'estimation des paramètres du modèle, divisé en deux groupes. La première concerne le calcul des vitesses des écoulements et l'autre la détermination de la capacité d'infiltration initiale et finale pour chaque type de sol. Les résultats validés avec l'équation de Nash montrent une bonne corrélation entre les débits simulés et ceux observés.

Estimation of glomerular filtration rate in hospitalized patients : are we overestimating renal function?

Estimer la filtration glomérulaire chez les personnes âgées, tout en tenant compte de la difficulté supplémentaire d'évaluer leur masse musculaire, est difficile et particulièrement important pour la prescription de médicaments. Le taux plasmatique de la creatinine dépend à la fois de la fraction d'élimination rénale et extra-rénale et de la masse musculaire. Actuellement, pour estimer là filtration glomérulaire différentes formules sont utilisées, qui se fondent principalement sur la valeur de la créatinine. Néanmoins, en raison de la fraction éliminée par les voies tubulaires et intestinales la clairance de la créatinine surestime généralement le taux de filtration glomérulaire (GFR). Le but de cette étude est de vérifier la fiabilité de certains marqueurs et algorithmes de la fonction rénale actuellement utilisés et d'évaluer l'avantage additionnel de prendre en considération la masse musculaire mesurée par la bio-impédance dans une population âgée (> 70 ans) et avec une fonction rénale chronique compromise basée sur MDRD eGFR (CKD stades lll-IV). Dans cette étude, nous comparons 5 équations développées pour estimer la fonction rénale et basées respectivement sur la créatinine sérique (Cockcroft et MDRD), la cystatine C (Larsson), la créatinine combinée à la bêta-trace protéine (White), et la créatinine ajustée à la masse musculaire obtenue par analyse de la bio-impédance (MacDonald). La bio-impédance est une méthode couramment utilisée pour estimer la composition corporelle basée sur l'étude des propriétés électriques passives et de la géométrie des tissus biologiques. Cela permet d'estimer les volumes relatifs des différents tissus ou des fluides dans le corps, comme par exemple l'eau corporelle totale, la masse musculaire (=masse maigre) et la masse grasse corporelle. Nous avons évalué, dans une population âgée d'un service interne, et en utilisant la clairance de l'inuline (single shot) comme le « gold standard », les algorithmes de Cockcroft (GFR CKC), MDRD, Larsson (cystatine C, GFR CYS), White (beta trace protein, GFR BTP) et Macdonald (GFR = ALM, la masse musculaire par bio-impédance. Les résultats ont montré que le GFR (mean ± SD) mesurée avec l'inuline et calculée avec les algorithmes étaient respectivement de : 34.9±20 ml/min pour l'inuline, 46.7±18.5 ml/min pour CKC, 47.2±23 ml/min pour CYS, 54.4±18.2ml/min pour BTP, 49±15.9 ml/min pour MDRD et 32.9±27.2ml/min pour ALM. Les courbes ROC comparant la sensibilité et la spécificité, l'aire sous la courbe (AUC) et l'intervalle de confiance 95% étaient respectivement de : CKC 0 68 (055-0 81) MDRD 0.76 (0.64-0.87), Cystatin C 0.82 (0.72-0.92), BTP 0.75 (0.63-0.87), ALM 0.65 (0.52-0.78). ' En conclusion, les algorithmes comparés dans cette étude surestiment la GFR dans la population agee et hospitalisée, avec des polymorbidités et une classe CKD lll-IV. L'utilisation de l'impédance bioelectrique pour réduire l'erreur de l'estimation du GFR basé sur la créatinine n'a fourni aucune contribution significative, au contraire, elle a montré de moins bons résultats en comparaison aux autres equations. En fait dans cette étude 75% des patients ont changé leur classification CKD avec MacDonald (créatinine et masse musculaire), contre 49% avec CYS (cystatine C), 56% avec MDRD,52% avec Cockcroft et 65% avec BTP. Les meilleurs résultats ont été obtenus avec Larsson (CYS C) et la formule de Cockcroft.

Quantile Estimation in Non-Stationary Streaming Data

We provide an incremental quantile estimator for Non-stationary Streaming Data. We propose a method for simultaneous estimation of multiple quantiles corresponding to the given probability levels from streaming data. Due to the limitations of the memory, it is not feasible to compute the quantiles by storing the data. So estimating the quantiles as the data pass by is the only possibility. This can be effective in network measurement. To provide the minimum of the mean-squared error of the estimation, we use parabolic approximation and for comparison we simulate the results for different number of runs and using both linear and parabolic approximations.

Experimental and clinical radiofrequency ablation: proposal for standardized description of coagulation size and geometry.

BACKGROUND: Radiofrequency (RF) ablation is used to obtain local control of unresectable tumors in liver, kidney, prostate, and other organs. Accurate data on expected size and geometry of coagulation zones are essential for physicians to prevent collateral damage and local tumor recurrence. The aim of this study was to develop a standardized terminology to describe the size and geometry of these zones for experimental and clinical RF. METHODS: In a first step, the essential geometric parameters to accurately describe the coagulation zones and the spatial relationship between the coagulation zones and the electrodes were defined. In a second step, standard terms were assigned to each parameter. RESULTS: The proposed terms for single-electrode RF ablation include axial diameter, front margin, coagulation center, maximal and minimal radius, maximal and minimal transverse diameter, ellipticity index, and regularity index. In addition a subjective description of the general shape and regularity is recommended. CONCLUSIONS: Adoption of the proposed standardized description method may help to fill in the many gaps in our current knowledge of the size and geometry of RF coagulation zones.

Concentrations of resveratrol and derivatives in foods and estimation of dietary intake in a Spanish population: European Prospective Investigation into Cancer and Nutrition (EPIC)-Spain cohort

Resveratrol has been shown to have beneficial effects on diseases related to oxidant and/or inflammatory processes and extends the lifespan of simple organisms including rodents. The objective of the present study was to estimate the dietary intake of resveratrol and piceid (R&P) present in foods, and to identify the principal dietary sources of these compounds in the Spanish adult population. For this purpose, a food composition database (FCDB) of R&P in Spanish foods was compiled. The study included 40 685 subjects aged 3564 years from northern and southern regions of Spain who were included in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Spain cohort. Usual food intake was assessed by personal interviews using a computerised version of a validated diet history method. An FCDB with 160 items was compiled. The estimated median and mean of R&P intake were 100 and 933 mg/d respectively. Approximately, 32% of the population did not consume RΠ The most abundant of the four stilbenes studied was trans-piceid (53·6 %), followed by trans-resveratrol (20·9 %), cis-piceid (19·3 %) and cis-resveratrol (6·2 %). The most important source of R&P was wines (98·4 %) and grape and grape juices (1·6 %), whereas peanuts, pistachios and berries contributed to less than 0·01 %. For this reason the pattern of intake of R&P was similar to the wine pattern. This is the first time that R&P intake has been estimated in a Mediterranean country.

Robust Estimators of the Generalized Log-Gamma Distribution

We propose robust estimators of the generalized log-gamma distribution and, more generally, of location-shape-scale families of distributions. A (weighted) Q tau estimator minimizes a tau scale of the differences between empirical and theoretical quantiles. It is n(1/2) consistent; unfortunately, it is not asymptotically normal and, therefore, inconvenient for inference. However, it is a convenient starting point for a one-step weighted likelihood estimator, where the weights are based on a disparity measure between the model density and a kernel density estimate. The one-step weighted likelihood estimator is asymptotically normal and fully efficient under the model. It is also highly robust under outlier contamination. Supplementary materials are available online.

Covariance Matrix Estimation and Mean-Variance Optimization in application to International Diversification

Tutkimus keskittyy kansainväliseen hajauttamiseen suomalaisen sijoittajan näkökulmasta. Tutkimuksen toinen tavoite on selvittää tehostavatko uudet kovarianssimatriisiestimaattorit minimivarianssiportfolion optimointiprosessia. Tavallisen otoskovarianssimatriisin lisäksi optimoinnissa käytetään kahta kutistusestimaattoria ja joustavaa monimuuttuja-GARCH(1,1)-mallia. Tutkimusaineisto koostuu Dow Jonesin toimialaindekseistä ja OMX-H:n portfolioindeksistä. Kansainvälinen hajautusstrategia on toteutettu käyttäen toimialalähestymistapaa ja portfoliota optimoidaan käyttäen kahtatoista komponenttia. Tutkimusaieisto kattaa vuodet 1996-2005 eli 120 kuukausittaista havaintoa. Muodostettujen portfolioiden suorituskykyä mitataan Sharpen indeksillä. Tutkimustulosten mukaan kansainvälisesti hajautettujen investointien ja kotimaisen portfolion riskikorjattujen tuottojen välillä ei ole tilastollisesti merkitsevää eroa. Myöskään uusien kovarianssimatriisiestimaattoreiden käytöstä ei synnytilastollisesti merkitsevää lisäarvoa verrattuna otoskovarianssimatrisiin perustuvaan portfolion optimointiin.