A Levinson algorithm based on an isometric transformation of Durbin`s

Starting from the Durbin algorithm in polynomial space with an inner product defined by the signal autocorrelation matrix, an isometric transformation is defined that maps this vector space into another one where the Levinson algorithm is performed. Alternatively, for iterative algorithms such as discrete all-pole (DAP), an efficient implementation of a Gohberg-Semencul (GS) relation is developed for the inversion of the autocorrelation matrix which considers its centrosymmetry. In the solution of the autocorrelation equations, the Levinson algorithm is found to be less complex operationally than the procedures based on GS inversion for up to a minimum of five iterations at various linear prediction (LP) orders.

Distributed power control algorithm for multiple access systems based on Verhulst model

In this paper the continuous Verhulst dynamic model is used to synthesize a new distributed power control algorithm (DPCA) for use in direct sequence code division multiple access (DS-CDMA) systems. The Verhulst model was initially designed to describe the population growth of biological species under food and physical space restrictions. The discretization of the corresponding differential equation is accomplished via the Euler numeric integration (ENI) method. Analytical convergence conditions for the proposed DPCA are also established. Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations. The simulation results are compared with two other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal of Uykan and Koivo. Under estimated errors conditions, the proposed DPCA exhibits smaller discrepancy from the optimum power vector solution and better convergence (under fixed and adaptive convergence factor) than the classic and sigmoidal DPCAs. (C) 2010 Elsevier GmbH. All rights reserved.

The Policy Iteration Algorithm for Average Continuous Control of Piecewise Deterministic Markov Processes

The main goal of this paper is to apply the so-called policy iteration algorithm (PIA) for the long run average continuous control problem of piecewise deterministic Markov processes (PDMP`s) taking values in a general Borel space and with compact action space depending on the state variable. In order to do that we first derive some important properties for a pseudo-Poisson equation associated to the problem. In the sequence it is shown that the convergence of the PIA to a solution satisfying the optimality equation holds under some classical hypotheses and that this optimal solution yields to an optimal control strategy for the average control problem for the continuous-time PDMP in a feedback form.

Optimization of the Topology of Electric Energy Distribution Networks by Using Algorithm Inspired on Ant Behaviors

An algorithm inspired on ant behavior is developed in order to find out the topology of an electric energy distribution network with minimum power loss. The algorithm performance is investigated in hypothetical and actual circuits. When applied in an actual distribution system of a region of the State of Sao Paulo (Brazil), the solution found by the algorithm presents loss lower than the topology built by the concessionary company.

Avoiding Divergence in the Shalvi-Weinstein Algorithm

The most popular algorithms for blind equalization are the constant-modulus algorithm (CMA) and the Shalvi-Weinstein algorithm (SWA). It is well-known that SWA presents a higher convergence rate than CMA. at the expense of higher computational complexity. If the forgetting factor is not sufficiently close to one, if the initialization is distant from the optimal solution, or if the signal-to-noise ratio is low, SWA can converge to undesirable local minima or even diverge. In this paper, we show that divergence can be caused by an inconsistency in the nonlinear estimate of the transmitted signal. or (when the algorithm is implemented in finite precision) by the loss of positiveness of the estimate of the autocorrelation matrix, or by a combination of both. In order to avoid the first cause of divergence, we propose a dual-mode SWA. In the first mode of operation. the new algorithm works as SWA; in the second mode, it rejects inconsistent estimates of the transmitted signal. Assuming the persistence of excitation condition, we present a deterministic stability analysis of the new algorithm. To avoid the second cause of divergence, we propose a dual-mode lattice SWA, which is stable even in finite-precision arithmetic, and has a computational complexity that increases linearly with the number of adjustable equalizer coefficients. The good performance of the proposed algorithms is confirmed through numerical simulations.

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.

Hardware/firmware implementation of a soft sensor using an improved version of a fuzzy identification algorithm

This paper presents the design and implementation of an embedded soft sensor, i. e., a generic and autonomous hardware module, which can be applied to many complex plants, wherein a certain variable cannot be directly measured. It is implemented based on a fuzzy identification algorithm called ""Limited Rules"", employed to model continuous nonlinear processes. The fuzzy model has a Takagi-Sugeno-Kang structure and the premise parameters are defined based on the Fuzzy C-Means (FCM) clustering algorithm. The firmware contains the soft sensor and it runs online, estimating the target variable from other available variables. Tests have been performed using a simulated pH neutralization plant. The results of the embedded soft sensor have been considered satisfactory. A complete embedded inferential control system is also presented, including a soft sensor and a PID controller. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.

The single machine earliness and tardiness scheduling problem: lower bounds and a branch-and-bound algorithm

This paper addresses the single machine scheduling problem with a common due date aiming to minimize earliness and tardiness penalties. Due to its complexity, most of the previous studies in the literature deal with this problem using heuristics and metaheuristics approaches. With the intention of contributing to the study of this problem, a branch-and-bound algorithm is proposed. Lower bounds and pruning rules that exploit properties of the problem are introduced. The proposed approach is examined through a computational comparative study with 280 problems involving different due date scenarios. In addition, the values of optimal solutions for small problems from a known benchmark are provided.

The sorption of toxic elements onto natural zeolite, synthetic goethite and modified powdered block carbon

Inorganic elements analyses of Carapicuiba lake reveal that As, Cr, Pb and Mn are above the recommended drinking water standards. The mean total concentrations of toxic elements in surface water decrease in the order Mn > Cr > Pb > As. At elevated concentrations, toxic elements like Cr can accumulate in soils and enter the food chain, leading to serious health hazards and threatening the long-term sustainability of the local ecosystem. Absorbing materials has often been used to improve water quality. In this investigation three types of material were studied: the natural zeolite (mordenite); synthetic goethite and the powdered block carbon modified. The adsorption of Pb(2+) and Mn(2+) onto natural zeolite as a function of their concentrations was studied at 24 degrees C by varying the metal concentration from 100 to 400 mg L(-1) while keeping all other parameters constant. The low-cost zeolites removed Pb from water without any pretreatment at pH values <6. The maximum adsorption attained was as follows: Pb(2+) 78.7% and Mn(2+) 19.6%. The modified powdered block carbon effectively removed As(V) and Cr(VI) while goethite removed more chromate than arsenate in the pH range 5-6. Results of this study will be used to evaluate the application these materials for the treatment of the Carapicuiba lake`s water.

Electrochemical and spectroscopic characterization of screen-printed gold-based electrodes modified with self-assembled monolayers and Tc85 protein

This work investigates the formation of self-assembled monolayers (SAMs) of cystamine and cystamine-glutaraldehyde on a screen-printed electrode, and the immobilization of the Tc85 protein (from Trypanosoma cruzi) on these monolayers. The methods used included infrared techniques, cyclic voltammetry, and electrochemical impedance spectroscopy. The electrochemical studies were performed at pH 6.9 in 0.1 mol L(-1) phosphate buffer solution containing Fe(CN)(6)(-3/-4) redox species. The surface coverage (0) of the electrode was 0.10 (cystamine), 0.35 (cystamine-glutaraldehyde) and 0.84 (Tc85). Interpretation of electrochemical impedance spectroscopy results was based on a charge-transfer reaction involving Fe(CN)(6)(-3/-4) species at high frequencies, followed by a diffusion through the monolayers at lower frequencies. Estimates of the electrode surface coverage, active site radius, and distance between two adjacent sites assumed that charge transfer occurred at the active sites, and that there was a planar diffusion of redox species to these sites. (C) 2009 Elsevier B.V. All rights reserved.

A modified epidemiological model for computer viruses

Since the computer viruses pose a serious problem to individual and corporative computer systems, a lot of effort has been dedicated to study how to avoid their deleterious actions, trying to create anti-virus programs acting as vaccines in personal computers or in strategic network nodes. Another way to combat viruses propagation is to establish preventive policies based on the whole operation of a system that can be modeled with population models, similar to those that are used in epidemiological studies. Here, a modified version of the SIR (Susceptible-Infected-Removed) model is presented and how its parameters are related to network characteristics is explained. Then, disease-free and endemic equilibrium points are calculated, stability and bifurcation conditions are derived and some numerical simulations are shown. The relations among the model parameters in the several bifurcation conditions allow a network design minimizing viruses risks. (C) 2009 Elsevier Inc. All rights reserved.

Biogenic modified silica as a sorbent of cadmium ions: Preparation and characterization

This work describes the preparation and characterization of biogenic modified silica from rice hull ash and its use as a sorbent of cadmium ions. Thus, an agro-industrial residue has been used to produce a new adsorbent product which is able to remove toxic elements. Mesoporous biogenic silica was obtained by alkaline extraction of sodium silicate by hydrolysis with the sol-gel process, and it was modified with salen using 1,2-dichloroethane as a spacer. The surface area of the silica was measured by nitrogen adsorption/desorption analysis. Surface modification was measured by Fourier transform infrared spectroscopy. The degree of functionalization was obtained by elemental analysis. This work showed that biogenic modified silica can be produced in aqueous media from rice hull ash using a simple method, providing an alternative method for adsorbent preparation. Thermogravimetric analysis showed that the salen-modified silica is stable up to 209 C. The modified silica displays appropriate structural characteristics for an adsorbent. The cylindrical pores, open at both ends, allow free diffusion of cadmium ions to the adsorption sites on the silica surface. The surface modification increases cadmium adsorption on the silica surface 100-fold. The salen-modified silica showed specific adsorption for Cd2+ of 44.52 mg/g SiO2 at cadmium concentration of 100 mg/l.

Inverse aerodynamic design applications using the MGM hybrid formulation

The well-known modified Garabedian-Mcfadden (MGM) method is an attractive alternative for aerodynamic inverse design, for its simplicity and effectiveness (P. Garabedian and G. Mcfadden, Design of supercritical swept wings, AIAA J. 20(3) (1982), 289-291; J.B. Malone, J. Vadyak, and L.N. Sankar, Inverse aerodynamic design method for aircraft components, J. Aircraft 24(2) (1987), 8-9; Santos, A hybrid optimization method for aerodynamic design of lifting surfaces, PhD Thesis, Georgia Institute of Technology, 1993). Owing to these characteristics, the method has been the subject of several authors over the years (G.S. Dulikravich and D.P. Baker, Aerodynamic shape inverse design using a Fourier series method, in AIAA paper 99-0185, AIAA Aerospace Sciences Meeting, Reno, NV, January 1999; D.H. Silva and L.N. Sankar, An inverse method for the design of transonic wings, in 1992 Aerospace Design Conference, No. 92-1025 in proceedings, AIAA, Irvine, CA, February 1992, 1-11; W. Bartelheimer, An Improved Integral Equation Method for the Design of Transonic Airfoils and Wings, AIAA Inc., 1995). More recently, a hybrid formulation and a multi-point algorithm were developed on the basis of the original MGM. This article discusses applications of those latest developments for airfoil and wing design. The test cases focus on wing-body aerodynamic interference and shock wave removal applications. The DLR-F6 geometry is picked as the baseline for the analysis.

Identification of protein coding regions using the modified Gabor-wavelet transform

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

The beta modified Weibull distribution

A five-parameter distribution so-called the beta modified Weibull distribution is defined and studied. The new distribution contains, as special submodels, several important distributions discussed in the literature, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among others. The new distribution can be used effectively in the analysis of survival data since it accommodates monotone, unimodal and bathtub-shaped hazard functions. We derive the moments and examine the order statistics and their moments. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.