Stochastic stability analysis for the constant-modulus algorithm

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.

Coarse-grid higher order finite-difference time-domain algorithm with low dispersion errors

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.

Development and fabrication of an optimized thermo-electro-optic device using a Mach-Zehnder interferometer

The development and fabrication of a thermo-electro-optic sensor using a Mach-Zehnder interferometer and a resistive micro-heater placed in one of the device`s arms is presented. The Mach-Zehnder structure was fabricated on a single crystal silicon substrate using silicon oxynitride and amorphous hydrogenated silicon carbide films to form an anti-resonant reflective optical waveguide. The materials were deposited by Plasma enhanced chemical vapor deposition technique at low temperatures (similar to 320 degrees C). To optimize the heat transfer and increase the device response with current variation, part of the Mach-Zehnder sensor arm was suspended through front-side bulk micromachining of the silicon substrate in a KOH solution. With the temperature variation caused by the micro-heater, the refractive index of the core layer of the optical waveguide changes due to the thermo-optic effect. Since this variation occurs only in one of the Mach-Zehnder`s arm, a phase difference between the arms is produced, leading to electromagnetic interference. In this way, the current applied to the micro-resistor can control the device output optical power. Further, reactive ion etching technique was used in this work to define the device`s geometry, and a study of SF6 based etching rates on different composition of silicon oxynitride films is also presented. (C) 2007 Elsevier B.V. All rights reserved.

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.

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.

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.

Effects of 7-Epiclusianone on Streptococcus mutans and Caries Development in Rats

The aim of this study was to evaluate the effects of 7-epiclusianone (7-epi) on specific virulence attributes of Streptococcus mutans in vitro and on development of dental caries in vivo. 7-Epi was obtained and purified from fruits of Rheedia brasiliensis. We investigated its influence on surface-adsorbed glucosyltransferase (Gtf) B activity, acid production, and viability of S. mutans in biofilms, as well as on caries development using a rodent model. 7-Epi (100 mu g/mL) significantly reduced the activity of surface-adsorbed GtfB (up to 48.0 +/- 1.8 of inhibition at 100 mu g/mL) and glyco-lytic pH-drop by S. mutans in biofilms (125 and 250 mu g/mL) (vs. vehicle control, p < 0.05). In contrast, the test compound did not significantly affect the bacterial viability when compared to vehicle control (15% ethanol, p > 0.05). Wistar rats treated topically with 7-epi (twice daily, 60-s exposure) showed significantly smaller number of and less severe smooth-and sulcal-surface carious lesions (p < 0.05), without reducing the S. mutans viable population from the animals` dental biofilms. In conclusion, the natural compound 7-epiclusianone may be a potentially novel pharmacological agent to prevent and control dental caries disease.

Anatomical development of the pericarp and seed of Oncidium flexuosum Sims (ORCHIDACEAE)

Interpretation of the anatomical structure of the ovary and fruit of the Orchidaceae family is still controversial, which makes it difficult to understand the development and dehiscence of the fruit. The genus Oncidium is polyphyletic and is currently the subject of taxonomic studies. In this study, we have investigated the anatomical development of the pericarp and seed of Oncidium flexuosum Sims to determine important diagnostic characters that, along with molecular data, can assist in defining this group. We have found a new anatomical characteristic of the family: the presence of precursor cells for fruit dehiscence, which were visible from the beginning of development and located on the outer walls of the sterile valves. In contrast with what has been observed by different authors with other species, in the mature fruit of O. flexuosum, only the endocarp of the fertile valves and a few cells near the exocarp and the vascular bundle in the sterile valves show parietal thickening, while the rest remains parenchymatous. During the development of the ovule and embryo, we have shown that the embryonic sac of this species has eight nuclei and that the embryo has a long and elaborate suspensor. (C) 2011 Elsevier GmbH. All rights reserved.

Sugar and ethanol production as a rural development strategy in Brazil: Evidence from the state of Sao Paulo

Sugar and ethanol production are key components of Brazil`s rural development and energy strategies, yet in recent years sugar production has been widely criticized for its environmental and labor practices. This study examines the relationship between rural development and sugarcane, ethanol, and cattle production in the state of Sao Paulo. Our results suggest that the value added components of sugarcane production, which include sugar refining and ethanol production, may have a strong positive affect on local human development in comparison to primary agricultural production activities and other land uses. These results imply that sugar production, when accompanied by a local processing industry can stimulate rural development. However, this paper also highlights the significant environmental and social harms generated by the sugar industry at large, which may undermine its development benefits if not addressed. (C) 2011 Elsevier Ltd. All rights reserved.