Improving the tracking capability of adaptive filters via convex combination

As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.

Valve friction and nonlinear process model closed-loop identification

Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.

On state representations of nonlinear implicit systems

This work considers a semi-implicit system A, that is, a pair (S, y), where S is an explicit system described by a state representation (x)over dot(t) = f(t, x(t), u(t)), where x(t) is an element of R(n) and u(t) is an element of R(m), which is subject to a set of algebraic constraints y(t) = h(t, x(t), u(t)) = 0, where y(t) is an element of R(l). An input candidate is a set of functions v = (v(1),.... v(s)), which may depend on time t, on x, and on u and its derivatives up to a Finite order. The problem of finding a (local) proper state representation (z)over dot = g(t, z, v) with input v for the implicit system Delta is studied in this article. The main result shows necessary and sufficient conditions for the solution of this problem, under mild assumptions on the class of admissible state representations of Delta. These solvability conditions rely on an integrability test that is computed from the explicit system S. The approach of this article is the infinite-dimensional differential geometric setting of Fliess, Levine, Martin, and Rouchon (1999) (`A Lie-Backlund Approach to Equivalence and Flatness of Nonlinear Systems`, IEEE Transactions on Automatic Control, 44(5), (922-937)).

Using bifurcations in the determination of lock-in ranges for third-order phase-locked loops

Transmission and switching in digital telecommunication networks require distribution of precise time signals among the nodes. Commercial systems usually adopt a master-slave (MS) clock distribution strategy building slave nodes with phase-locked loop (PLL) circuits. PLLs are responsible for synchronizing their local oscillations with signals from master nodes, providing reliable clocks in all nodes. The dynamics of a PLL is described by an ordinary nonlinear differential equation, with order one plus the order of its internal linear low-pass filter. Second-order loops are commonly used because their synchronous state is asymptotically stable and the lock-in range and design parameters are expressed by a linear equivalent system [Gardner FM. Phaselock techniques. New York: John Wiley & Sons: 1979]. In spite of being simple and robust, second-order PLLs frequently present double-frequency terms in PD output and it is very difficult to adapt a first-order filter in order to cut off these components [Piqueira JRC, Monteiro LHA. Considering second-harmonic terms in the operation of the phase detector for second order phase-locked loop. IEEE Trans Circuits Syst [2003;50(6):805-9; Piqueira JRC, Monteiro LHA. All-pole phase-locked loops: calculating lock-in range by using Evan`s root-locus. Int J Control 2006;79(7):822-9]. Consequently, higher-order filters are used, resulting in nonlinear loops with order greater than 2. Such systems, due to high order and nonlinear terms, depending on parameters combinations, can present some undesirable behaviors, resulting from bifurcations, as error oscillation and chaos, decreasing synchronization ranges. In this work, we consider a second-order Sallen-Key loop filter [van Valkenburg ME. Analog filter design. New York: Holt, Rinehart & Winston; 1982] implying a third order PLL The resulting lock-in range of the third-order PLL is determined by two bifurcation conditions: a saddle-node and a Hopf. (C) 2008 Elsevier B.V. All rights reserved.

The Cramer-Rao bound for initial conditions estimation of chaotic orbits

We derive the Cramer-Rao Lower Bound (CRLB) for the estimation of initial conditions of noise-embedded orbits produced by general one-dimensional maps. We relate this bound`s asymptotic behavior to the attractor`s Lyapunov number and show numerical examples. These results pave the way for more suitable choices for the chaotic signal generator in some chaotic digital communication systems. (c) 2006 Published by Elsevier Ltd.

Jointly multi-user detection and channel estimation with genetic algorithm

This work aims at proposing the use of the evolutionary computation methodology in order to jointly solve the multiuser channel estimation (MuChE) and detection problems at its maximum-likelihood, both related to the direct sequence code division multiple access (DS/CDMA). The effectiveness of the proposed heuristic approach is proven by comparing performance and complexity merit figures with that obtained by traditional methods found in literature. Simulation results considering genetic algorithm (GA) applied to multipath, DS/CDMA and MuChE and multi-user detection (MuD) show that the proposed genetic algorithm multi-user channel estimation (GAMuChE) yields a normalized mean square error estimation (nMSE) inferior to 11%, under slowly varying multipath fading channels, large range of Doppler frequencies and medium system load, it exhibits lower complexity when compared to both maximum likelihood multi-user channel estimation (MLMuChE) and gradient descent method (GrdDsc). A near-optimum multi-user detector (MuD) based on the genetic algorithm (GAMuD), also proposed in this work, provides a significant reduction in the computational complexity when compared to the optimum multi-user detector (OMuD). In addition, the complexity of the GAMuChE and GAMuD algorithms were (jointly) analyzed in terms of number of operations necessary to reach the convergence, and compared to other jointly MuChE and MuD strategies. The joint GAMuChE-GAMuD scheme can be regarded as a promising alternative for implementing third-generation (3G) and fourth-generation (4G) wireless systems in the near future. Copyright (C) 2010 John Wiley & Sons, Ltd.

On state representations of time-varying nonlinear systems

This work considers a nonlinear time-varying system described by a state representation, with input u and state x. A given set of functions v, which is not necessarily the original input u of the system, is the (new) input candidate. The main result provides necessary and sufficient conditions for the existence of a local classical state space representation with input v. These conditions rely on integrability tests that are based on a derived flag. As a byproduct, one obtains a sufficient condition of differential flatness of nonlinear systems. (C) 2009 Elsevier Ltd. All rights reserved.

Electron beam induced second-harmonic generation in Er(3+) doped PbO-GeO(2) glasses containing silver nanoparticles

Electron beam induced second harmonic generation (SHG) is studied in Er(3+) doped PbO-GeO(2) glasses containing silver nanoparticles with concentrations that are controlled by the heat-treatment of the samples. The SHG is observed at T = 4.2 K using a p-polarized laser beam at 1064 nm. Enhancement of the SHG is observed in the samples that are submitted to electron beam incidence. The highest value of the nonlinear susceptibility, 2.08 pm/V, is achieved for the sample heat-treated during 72 h and submitted to an electron beam current of 15 nA. The samples that were not exposed to the electron beam present a susceptibility of a parts per thousand 0.5 pm/V.

Harmonic distortion analysis of double gate graded-channel MOSFETs operating in saturation

In this work we present an analysis of harmonic distortion (HD) in graded-channel (GC) gate-all-a round (GAA) devices operating in saturation region for analog applications. The study has been performed through device characterization and two-dimensional process and device simulations. The overall study has been done on the total and third order HDs. When applied in the saturation regime as an amplifier, the GC outperforms conventional GAA transistors presenting simultaneously higher transconductance, lower drain output conductance and more than 15 dB improved linearity. The influence of channel length reduction on the H D is also analyzed. Although slight linearity degradation is observed in both the conventional and the GC devices when reducing the channel length, the HD presented by the GC transistor is significantly lower than the one showed by conventional device for any Studied channel length. This allows AC input signal amplitude up to 20 times higher than the conventional GAA for a same specified distortion level. (C) 2008 Elsevier Ltd. All rights reserved.

Floristic composition of seasonal riparian forests in Mato Grosso do Sul State, Brazil

(Floristic composition of seasonal riparian forests in Mato Grosso do Sit] State, Brazil). This Study aimed to characterize the floristic composition in two stretches of seasonal semideciduous forest associated with the Formoso River, Bonito, Mato Grosso do Sul State, and in three stretches of seasonal deciduous and semideciduous forests associated with the Salobra, Salobrinha and Perdido rivers in Bodoquena Plateau National Park (76,481 ha) - the only Federal Conservation unit with Integral Protection in the state of Mato Grosso do Sul. The floristic survey was carried out monthly from October/2004 to March/2006, where flowering and fruiting phanerogams were collected by the method of evaluation time. The floristic survey resulted in 56 families, 184 genera and 307 species. Of the total number of species, 68% were trees, 17% shrubs, 14% lianas and only 1% palms. The Fabaceae family (Leguminosae), represented by 51 (16.6%) species, was the most species-rich. These results increase our knowledge of the Mato Grosso do Sul flora and its geographic distribution, thus emphasizing the need for conservation of these riparian forests and providing subsidies for restoration projects of the degraded areas around the conservation unit and permanent protection areas (APPs) of regional rivers.

Forest restoration in an indigenous land considering a forest remnant influence (Avai, Sao Paulo State, Brazil)

The expansion of agricultural and pasture areas over native forest areas has been broadly documented and represents the main cause of deforestation that has occurred for the last decades. Such reality is not different in indigenous lands, and has been considered as an important obstacle for individuals who directly depend upon the appropriate management of natural resources to maintain their traditions. We investigated the seed rain, seed bank and natural regeneration of native woody species within a degraded pasture land in different distances from an adjacent seasonal semideciduous forest fragment to define methodological procedures based on ecological processes that might subsidize forest restoration in an indigenous land. Most seeds and seedlings picked from the seed rain and seed bank belonged to anemochoric and autochoric dispersing shrubby and herbaceous species originated in the pasture land. The woody species regeneration, on the other hand, reached higher levels, in terms of abundance and richness, as the forest fragment became closer. Zoochoric dispersal was predominant among such species and was mainly detected closer to the forest fragment. Several woody species picked in the forest fragment were also found in the pasture land, thus reinforcing their important role in supplying propagules and easing the successional process. (c) 2007 Elsevier B.V. All rights reserved.

Extensions of discrete triangular distributions and boundary bias in kernel estimation for discrete functions

Asymmetric discrete triangular distributions are introduced in order to extend the symmetric ones serving for discrete associated kernels in the nonparametric estimation for discrete functions. The extension from one to two orders around the mode provides a large family of discrete distributions having a finite support. Establishing a bridge between Dirac and discrete uniform distributions, some different shapes are also obtained and their properties are investigated. In particular, the mean and variance are pointed out. Applications to discrete kernel estimators are given with a solution to a boundary bias problem. (C) 2010 Elsevier B.V. All rights reserved.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

The effectiveness of Eucalyptus barrier in containing the edge effect on a subtropical forest fragment in the state of Sao Paulo, Brazil

Edge effects resulting from isolation and subsequent microclimatic changes are one of the most important threats to the forest fragments conservation. The efficiency of maintaining a barrier formed by three rows of Eucalyptus along the edge of a subtropical seasonal semi deciduous forest fragment, surrounded by Eucalyptus monoculture, was evaluated as a way of softening the microclimatic changes (light intensity, temperature and relative humidity) and the impacts of eucalypt mechanized harvesting on the native vegetation along the contact zone between the forest fragment and the plantation. The Eucalyptus barrier was effective in softening the microclimate. Light intensity was 35% lower in the presence of the barrier. The barrier also provided a reduction of 1 C in air temperature and increased in 3.4% in relative humidity throughout the year. The barrier was also effective in preventing the impact on native vegetation, avoiding damage to adult trees and preserving the regenerating forest stratum near the border, which was reduced to less than 20% in density and 50% in richness, with no such barrier. The barrier of Eucalyptus may, therefore, be recommended as an effective method to minimize the impacts of mechanized forest harvesting operations and mitigate the microclimatic conditions along the edge of forest fragments.