Computationally efficient high-order yule-walker frequency estimation

This paper introduces a novel high-order Yule-Walker (HOYW) method for estimating sinusoidal frequencies. the proposed method does not require singular value decomposition (SVD) of the data covariance matrix, has a computational complexity similar to the overdetermined Yule-Walker (OYW) method and a statistical accuracy close to that of the SVD-based HOYW method, and is easy to implement in recursive form since it involves only linear operations on the data. an example of the performance that can be achieved by an adaptive form of this new HOWY method in a time-varying scenario is also given.     

Multiple-symbol double-differential detection based on least-squares and generalized-likelihood ratio criteria

Two algorithms for double-differential detection of multiple phase-shift keying modulation are proposed, based on a least-squares criterion and a generalized-likelihood ratio test, respectively. While both algorithms take advantage of the performance gain obtained by observing the received signal over an observation interval longer than that required for symbol-by-symbol detection, the former has the important advantage of reduced implementation complexity, whereas the latter offers better performance.     

Combined instrumental variable and subspace fitting approach toparameter estimation of noisy input-output systems

The paper considers the problem of estimating the parameters of linear discrete-time systems from noise-corrupted input-output measurements, under fairly general conditions: the output and input noises may be auto-correlated and they may be cross-correlated as well. By using the instrumental-variable (IV) principle a covariance matrix is obtained, the singular vectors of which bear complete information on the parameters of the system under study. A weighted subspace fitting (WSF) procedure is then employed on the sample singular vectors to derive estimates of the parameters of the system. The combined IV-WSF method proposed in the present paper is noniterative and simple to use. Its large-sample statistical performance is analyzed in detail and the theoretical results so obtained are used to predict the behavior of the method in samples with practical lengths. Several numerical examples are included to show the agreement between the theoretically predicted and the empirically observed performances     

On the expectation of the product of four matrix-valued Gaussianrandom variables

The formula for the expectation of the product of four scalar real Gaussian random variables is generalized to matrix-valued (real or complex) Gaussian random variables. As an application of the extended formula, a simple derivation is presented of the covariance matrix of instrumental variable estimates of parameters in multivariable regression models     

Cyclic minimizers, majorization techniques, and the expectation-maximization algorithm: a refresher

Many parameter estimation problems in signal processing can be reduced to the task of minimizing a function of the unknown parameters. This task is difficult owing to the existence of possibly local minima and the sharpness of the global minimum. In this article we review three approaches that can be used to minimize functions of the type encountered in parameter estimation problems. The first two approaches, the cyclic minimization and the majorization technique, are quite general, whereas the third one, the expectation-maximization (EM) algorithm, is tied to the use of the maximum likelihood (ML) method for parameter estimation. The article provides a quick refresher of the aforementioned approaches for a wide readership.     

Study of Capon method for array signal processing

The mean-square error (MSE) of Capon estimate of the directions-of-arrival (DOA) is established in the narrowband array processing case. An improved Capon-like DOA estimator is proposed and its MSE is studied as well. Performance comparisons between the standard and improved Capon DOA estimates, and between these two estimates and the linear prediction DOA estimate, are performed. It is concluded that the improved Capon-like method introduced in this paper provides more accurate DOA estimates in most cases.This work has been supported by the Swedish Research Council for Engineering Sciences under contract 91–676.     

Output‐based H2 optimal controllers for a class of discrete‐time stochastic linear systems with periodic coefficients

The aim of the paper is to present a design procedure of the optimal controller minimizing the H₂‐type norm of discrete‐time stochastic linear systems with periodic coefficients simultaneously affected by a nonhomogeneous but periodic Markov chain and state and control multiplicative white noise perturbations. Firstly, two H₂‐type norms for the linear stochastic systems under consideration were introduced. These H₂‐type norms may be viewed as measures of the effect of the additive white noise perturbations on the regulated output of the considered system. Before deriving of the state space representation of the optimal controller, some useful formulae of the two H₂‐type norms were obtained. These formulae are expressed in terms of periodic solutions of some suitable linear equations and are derived in the absence of some additional assumptions regarding the Markov chain other than the periodicity of the sequence of the transition probability matrices. Further, it is shown that the optimal H₂ controller depends on the stabilizing solutions of some specific systems of coupled Riccati equations, which generalize the well‐known control and filtering equations from linear time invariant case. For the readers convenience, the paper presents iterative numerical algorithms for the computations of the stabilizing solutions of these Riccati type systems. The theoretical developments are illustrated by numerical examples. Copyright © 2014 John Wiley & Sons, Ltd.     

Quantifying eventual consistency with PBS

Data store replication results in a fundamental trade-off between operation latency and data consistency. At the weak end of the consistency spectrum is eventual consistency providing no limit to the staleness of data returned. However, anecdotally, eventual consistency is often “good enough” for practitioners given its latency and availability benefits. In this work, we explain why eventually consistent systems are regularly acceptable in practice, analyzing both the staleness of data they return and the latency benefits they offer. We introduce Probabilistically Bounded Staleness (PBS), a consistency model which provides expected bounds on data staleness with respect to both versions and wall clock time. We derive a closed-form solution for versioned staleness as well as model real-time staleness under Internet-scale production workloads for a large class of quorum-replicated, Dynamo-style stores. Using PBS, we measure the latency–consistency trade-off for partial, non-overlapping quorum systems, including limited multi-object operations. We quantitatively demonstrate how and why eventually consistent systems frequently return consistent data within tens of milliseconds while offering significant latency benefits.     

Surface properties and biocompatibility of cellulose acetates

The article describes some properties of cellulose acetates (CAs) with different substitution degrees. The hydrophilic/hydrophobic properties, morphological aspects, and interface properties with red blood cells and platelets are affected by the substitution degree, synthesis conditions, history of the formed films from solutions in acetone/water nonsolvent/nonsolvent mixtures, and low pressure plasma treatment. The results obtained are useful in biomedical applications, including evaluation of bacterial adhesion onto surfaces, or utilization of CA for semipermeable membranes. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012