Implementation of two-stage Hopfield model and its application in nonlinear systems

This paper presents an efficient neural network for solving constrained nonlinear optimization problems. More specifically, a two-stage neural network architecture is developed and its internal parameters are computed using the valid-subspace technique. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty or weighting parameters for its initialization.

Signal-flow graphs: Direct method of reduction and MATLAB implementation

Block diagrams and signal-flow graphs are used to represent and to obtain the transfer function of interconnected systems. The reduction of signal-flow graphs is considered simpler than the reduction of block diagrams for systems with complex interrelationships. Signal-flow graphs reduction can be made without graphic manipulations of diagrams, and it is attractive for a computational implementation. In this paper the authors propose a computational method for direct reduction of signal-flow graphs. This method uses results presented in this paper about the calculation of literal determinants without symbolic mathematics tools. The Cramer's rule is applied for the solution of a set of linear equations, A program in MATLAB language for reduction of signal-flow graphs with the proposed method is presented.

Hardware implementation of an analog neural nonderivative optimizer

Analog neural systems that can automatically find the minimum value of the outputs of unknown analog systems, described by convex functions, are studied. When information about derivative or gradient are not used, these systems are called analog nonderivative optimizers. An electronic circuit for the analog neural nonderivative optimizer proposed by Teixeira and Zak, and its simulation with software PSPICE, is presented. With the simulation results and hardware implementation of the system, the validity of the proposed optimizer can be verified. These results are original, from the best of the authors knowledge.

Proportional controllers: Direct method for stability analysis and MATLAB implementation

In most cases, the cost of a control system increases based on its complexity. Proportional (P) controller is the simplest and most intuitive structure for the implementation of linear control systems. The difficulty to find the stability range of feedback systems with P controllers, using the Routh-Hurwitz criterion, increases with the order of the plant. For high order plants, the stability range cannot be easily obtained from the investigation of the coefficient signs in the first column of the Routh's array. A direct method for the determination of the stability range is presented. The method is easy to understand, to compute, and to offer the students a better comprehension on this subject. A program in MATLAB language, based on the proposed method, design examples, and class assessments, is provided in order to help the pedagogical issues. The method and the program enable the user to specify a decay rate and also extend to proportional-integral (PI), proportional-derivative (PD), and proportional-integral-derivative (PID) controllers.

On lag controllers: Design and implementation

Sometimes it is inconvenient or expensive to open the loop of a system to insert lag controllers-for instance, when this system is an open-loop system. A new controller structure where the loop is not opened, and that allows the design of lag controllers as in the case where one can open the loop, is presented. This result can be used by educators in undergraduate courses that deal with classic control system theory, because it allows a better comprehension of the concept of lag compensation and provides a new method for its design and implementation. An example illustrates the application of the proposed method.

A new implementation of population based incremental learning method for optimizations in electromagnetics

To enhance the global search ability of population based incremental learning (PBIL) methods, it is proposed that multiple probability vectors are to be included on available PBIL algorithms. The strategy for updating those probability vectors and the negative learning and mutation operators are thus re-defined correspondingly. Moreover, to strike the best tradeoff between exploration and exploitation searches, an adaptive updating strategy for the learning rate is designed. Numerical examples are reported to demonstrate the pros and cons of the newly implemented algorithm.

Mnltiloop Controller and Reference Generator for a Dynamic Voltage Restorer Implementation

This paper deals with the design and analysis of a Dynamic Voltage Restorer output voltage control. Such control is based on a multiloop strategy, with an inner current PID regulator and an outer P+Resonant voltage controller. The inner regulator is applied on the output inductor current. It will be also demonstrated how the load current behavior may influence in the DVR output voltage, which. justifies the need for the resonant controller. Additionally, it will be discussed the application of a modified algorithm for the identification of the DVR voltage references, which is based on a previously presented positive sequence detector. Since the studied three-phase DVR is assumed to be based on three identical H-bridge converters, all the analysis and design procedures were realized by means of single-phase equivalent circuits. The discussions and conclusions are supported by theoretical calculations, nonlinear simulations and some experimental results.

Surveillance Programme for Healthcare Associated Infections in the State of São Paulo, Brazil. Implementation and the first three years' results

Governmental programmes should be developed to collect and analyse data on healthcare associated infections (HAIs). This study describes the healthcare setting and both the implementation and preliminary results of the Programme for Surveillance of Healthcare Associated Infections in the State of São Paulo (PSHAISP), Brazil, from 2004 to 2006. Characterisation of the healthcare settings was carried out using a national database. The PSHAISP was implemented using components for acute care hospitals (ACH) or long term care facilities (LTCF). The components for surveillance in ACHs were surgical unit, intensive care unit and high risk nursery. The infections included in the surveillance were surgical site infection in clean surgery, pneumonia, urinary tract infection and device-associated bloodstream infections. Regarding the LTCF component, pneumonia, scabies and gastroenteritis in all inpatients were reported. In the first year of the programme there were 457 participating healthcare settings, representing 51.1% of the hospitals registered in the national database. Data obtained in this study are the initial results and have already been used for education in both surveillance and the prevention of HAI. The results of the PSHAISP show that it is feasible to collect data from a large number of hospitals. This will assist the State of São Paulo in assessing the impact of interventions and in resource allocation. (C) 2010 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.

An implementation of modified scatter search algorithm to transmission expansion planning

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Constraints implementation for IQML and mode direction-of-arrival estimators

The iterative quadratic maximum likelihood IQML and the method of direction estimation MODE are well known high resolution direction-of-arrival DOA estimation methods. Their solutions lead to an optimization problem with constraints. The usual linear constraint presents a poor performance for certain DOA values. This work proposes a new linear constraint applicable to both DOA methods and compare their performance with two others: unit norm and usual linear constraint. It is shown that the proposed alternative performs better than others constraints. The resulting computational complexity is also investigated.

An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology

This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian parameters (gain, center and width) is changed with programmable current source. Results obtained with PSPICE software is showed.

Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation

Linear mixed effects models have been widely used in analysis of data where responses are clustered around some random effects, so it is not reasonable to assume independence between observations in the same cluster. In most biological applications, it is assumed that the distributions of the random effects and of the residuals are Gaussian. This makes inferences vulnerable to the presence of outliers. Here, linear mixed effects models with normal/independent residual distributions for robust inferences are described. Specific distributions examined include univariate and multivariate versions of the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted and Markov chain Monte Carlo is used to carry out the posterior analysis. The procedures are illustrated using birth weight data on rats in a texicological experiment. Results from the Gaussian and robust models are contrasted, and it is shown how the implementation can be used for outlier detection. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process in linear mixed models, and they are easily implemented using data augmentation and MCMC techniques.

A new implementation of Population Based Incremental Learning method for optimization studies in electromagnetics

To enhance the global search ability of Population Based Incremental Learning (PBIL) methods, It Is proposed that multiple probability vectors are to be Included on available PBIL algorithms. As a result, the strategy for updating those probability vectors and the negative learning and mutation operators are redefined as reported. Numerical examples are reported to demonstrate the pros and cons of the newly Implemented algorithm. ©2006 IEEE.

Implementation of filters for image pre-processing for leaf analyses in plantations

In this work an image pre-processing module has been developed to extract quantitative information from plantation images with various degrees of infestation. Four filters comprise this module: the first one acts on smoothness of the image, the second one removes image background enhancing plants leaves, the third filter removes isolated dots not removed by the previous filter, and the fourth one is used to highlight leaves' edges. At first the filters were tested with MATLAB, for a quick visual feedback of the filters' behavior. Then the filters were implemented in the C programming language. At last, the module as been coded in VHDL for the implementation on a Stratix II family FPGA. Tests were run and the results are shown in this paper. © 2008 Springer-Verlag Berlin Heidelberg.

How the delphi and AHP methods are aiding to define the critical success factors priorities in a digital factory project implementation

Digital factory is a concept that offers a collaborative approach to enhance product and production engineering processes through simulation. Products, processes and resources are modeled to be used to develop and test the product conception and manufacturing processes, before their use in the real factory. The purpose of this paper is to present the steps to identify the Critical Success Factors (CSF) priorities in a digital factory project implementation in a Brazilian company and how the Delphi and AHP Methods are aiding to identify these CSF priorities. Copyright © 2008 SAE International.