983 resultados para Modified Berlekamp-Massey algorithm
Resumo:
The cost of a new ship design heavily depends on the principal dimensions of the ship; however, dimensions minimization often conflicts with the minimum oil outflow (in the event of an accidental spill). This study demonstrates one rational methodology for selecting the optimal dimensions and coefficients of form of tankers via the use of a genetic algorithm. Therein, a multi-objective optimization problem was formulated by using two objective attributes in the evaluation of each design, specifically, total cost and mean oil outflow. In addition, a procedure that can be used to balance the designs in terms of weight and useful space is proposed. A genetic algorithm was implemented to search for optimal design parameters and to identify the nondominated Pareto frontier. At the end of this study, three real ships are used as case studies. [DOI:10.1115/1.4002740]
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In this paper, the performance of bis-1, 2-(triethoxysilyl) ethane (BTSE) as a pre-treatment to protect the AA 2024-T3 against corrosion has been investigated by electrochemical impedance spectroscopy (EIS), potentiodynamic polarization curves, and the scanning vibrating electrode technique (SVET). The microstructural and morphological characterizations were carried out via scanning electron microscopy and atomic force microscopy and the chemical composition evaluated using contact angle measurements and X-ray photoelectron spectroscopy (XPS). The electrochemical results showed that the additives improved the anticorrosion properties of the coating. The chemical characterization indicated that additives contribute to an increased degree of surface coverage, as well as to a more complete reticulation. The SVET results evidenced the self-healing abilities of Ce ions. (C) 2009 Elsevier Ltd. All rights reserved.
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This paper presents the possible alternative removal options for the development of safe drinking water supply in the trace elements affected areas. Arsenic and chromium are two of the most toxic pollutants, introduced into natural waters from a variety of sources and causes various adverse effects on living bodies. Performance of three filter bed method was evaluated in the laboratory. Experiments have been conducted to investigate the sorption of arsenic and chromium on carbon steel and removal of trace elements from drinking water with a household filtration process. The affinity of the arsenic and chromium species for Fe/Fe(3)C (iron/iron carbide) sites is the key factor controlling the removal of the elements. The method is based on the use of powdered block carbon (PBC), powder carbon steel and ball ceramic in the ion-sorption columns as a cleaning process. The PBC modified is a satisfactory and practical sorbent for trace elements (arsenite and chromate) dissolved in water.
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In the last few years great efforts have been made in order to find and to develop environmentally friendly substitutes for Cr6+ pre-treatments applied on aluminium alloys used in the aircraft industry. Among the potential substitutes, silane layers have attracted considerable interest from researchers and from the industry. The present work investigates the anti-corrosion behaviour of (bis-1, 2-(triethoxysilyl) ethane (BTSE)) silane layers modified with Ce ions and/or silica nanoparticles applied on Al alloy 2024-T3 substrates. The corrosion behaviour was investigated in 0.1 M NaCl solution via d.c. polarization and electrochemical impedance spectroscopy (EIS). Contact angle measurements and XPS were used to assess information on the chemistry of the silane pre-treated surfaces. The results have shown that the introduction of additives improves the corrosion protection properties of the silane layer. (c) 2008 Elsevier Ltd. All rights reserved.
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This paper present the possible alternative options for the remove of trace elements from drinking water supplies in the trace. Arsenic and chromium are two of the most toxic pollutants, introduced into natural waters from a variety of sources and causing various adverse effects on living bodies. The performance of three filter bed methods was evaluated in the laboratory. Experiments were conducted to investigate the sorption of arsenic and chromium on carbon steel and removal of trace elements from drinking water with a household filtration process. The affinity of the arsenic and chromium species for Fe / Fe3C (iron / iron carbide) sites is the key factor controlling the removal of the elements. The method is based on the use of powdered block carbon, powder carbon steel and ceramic spheres in the ion-sorption columns as a cleaning process. The modified powdered block carbon is a satisfactory and economical sorbent for trace elements (arsenite and chromate) dissolved in water due to its low unit cost of about $23 and compatibility with the traditional household filtration system.
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We present a novel array RLS algorithm with forgetting factor that circumvents the problem of fading regularization, inherent to the standard exponentially-weighted RLS, by allowing for time-varying regularization matrices with generic structure. Simulations in finite precision show the algorithm`s superiority as compared to alternative algorithms in the context of adaptive beamforming.
Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm
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We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.
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This article presents a triple-mode bandpass filter using a modified circular patch resonator. Etched slots in the resonator split the TM(1, 1, 0)(z) degenerate fundamental modes and also perturb the TM(2, 1, 0)(z) mode, approximating their resonant frequencies to form a third-order bandpass filter. A 2.42 GHz centered filter was designed and fabricated. Experimental results showed a fractional bandwidth of 29%, return loss better than 16 dB, insertion loss of 0.5 dB, and good second harmonic band rejection. The filter exhibited a size reduction of 51% compared with a filter using an unperturbed circular patch resonator at the same frequency. (C) 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 178-182, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23950
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We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence, of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.
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Higher order (2,4) FDTD schemes used for numerical solutions of Maxwell`s equations are focused on diminishing the truncation errors caused by the Taylor series expansion of the spatial derivatives. These schemes use a larger computational stencil, which generally makes use of the two constant coefficients, C-1 and C-2, for the four-point central-difference operators. In this paper we propose a novel way to diminish these truncation errors, in order to obtain more accurate numerical solutions of Maxwell`s equations. For such purpose, we present a method to individually optimize the pair of coefficients, C-1 and C-2, based on any desired grid size resolution and size of time step. Particularly, we are interested in using coarser grid discretizations to be able to simulate electrically large domains. The results of our optimization algorithm show a significant reduction in dispersion error and numerical anisotropy for all modeled grid size resolutions. Numerical simulations of free-space propagation verifies the very promising theoretical results. The model is also shown to perform well in more complex, realistic scenarios.
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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.
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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.
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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.
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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.
Resumo:
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.