933 resultados para fuzzy-basis membership functions
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It seems that a dual location for vagal preganglionic neurones (VPNs) has important functional correlates in all vertebrates. This may be particularly the case with the central control exerted over the heart by cardiac VPNs (CVPNs). About 30 % of VPNs but up to 70 % of CVPNs are in the nucleus ambiguus (NA) of mammals. There is a similar proportional representation of VPNs between the major vagal nuclei in amphibians and turtles but in fish and crocodilians; the proportion of VPNs in the NA is closer to 10% and in some lizards and birds it is about 5%. However, the CVPNs are distributed unequally between these nuclei so that 45 % of the CVPNs are located in the NA of the dogfish, and about 30% in the NA of Xenopus and the duck. This topographical separation of CVPNs seems to be of importance in the central control of the heart. Cells in one location may show respiration-related activity (e.g those in the dorsal vagal nucleus (DVN) of dogfish and in the NA of mammals) while cells in the other locations do not. Their different activities and separate functions will be determined by their different afferent inputs from the periphery or from elsewhere in the CNS, which in turn will relate to their central topography. Thus, CVPNs in the NA of mammals receive inhibitory inputs from neighbouring inspiratory neurones, causing respiratory sinus arrythmia (RSA), and the CVPNs in the DVN of the dogfish may generate cardiorespiratory synchrony (CRS).
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The Generator Coordinate Hartree-Fock (GCHF) method is employed to generate uncontracted 15s and 18s11p gaussian basis sets for the H, C and O atoms, respectively. These basis sets are then contracted to 3s and 4s H atom and 6s5p, for C and O atoms by a standard procedure. For quality evaluation of contracted basis sets in molecular calculations, we have accomplished calculations of total and orbital energies in the Hartree-Fock-Roothaaii (HFR) approach for CH, C(2) and CO molecules. The results obtained with the uncontracted basis sets are compared with values obtained with the standard D95, 6-311G basis sets and with values reported in the literature. The 4s and 6s5p basis sets are enriched with polarization and diffuse functions for atoms of the parent neutral systems and of the enolates anions (cycloheptanone enolate, 2,5-dimethyleyelopentanone enolate, 4-heptanone enolate, and di-isopropyl ketone enolate) from the literature, in order to assess their performance in ab initio molecular calculations, and applied for calculations of electron affinities of the enolates. The calculations were performed at the DFT (BLYP and B3LYP) and HF levels and compared with the corresponding experimental values and with those obtained by using other 6-3 1 + +G((*)) and 6-311 + +G((*)) basis sets from literature. For the enolates studied, the differences between the electron affinities obtained with GCHF basis sets, at the B3LYP level, and the experimental values are -0.001, -0,014, -0.001, and -0.001 eV. (C) 2002 Elsevier B.V. B.V. All rights reserved.
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We present angular basis functions for the Schrödinger equation of two-electron systems in hyperspherical coordinates. By using the hyperspherical adiabatic approach, the wave functions of two-electron systems are expanded in analytical functions, which generalizes the Jacobi polynomials. We show that these functions, obtained by selecting the diagonal terms of the angular equation, allow efficient diagonalization of the Hamiltonian for all values of the hyperspherical radius. The method is applied to the determination of the 1S e energy levels of the Li + and we show that the precision can be improved in a systematic and controllable way. ©2000 The American Physical Society.
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This paper presents a new methodology for the adjustment of fuzzy inference systems, which uses technique based on error back-propagation method. The free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules, are automatically adjusted. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through estimation of time series and by a mathematical modeling problem. More specifically, the Mackey-Glass chaotic time series is used for the validation of the proposed methodology. © Springer-Verlag Berlin Heidelberg 2007.
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An analog circuit that implements a radial basis function network is presented. The proposed circuit allows the adjustment of all shape parameters of the radial functions, i.e., amplitude, center and width. The implemented network was applied to the linearization of a nonlinear circuit, a voltage controlled oscillator (VCO). This application can be classified as an open-loop control in which the network plays the role of the controller. Experimental results have proved the linearization capability of the proposed circuit. Its performance can be improved by using a network with more basis functions. Copyright 2007 ACM.
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A RBFN implemented with quantized parameters is proposed and the relative or limited approximation property is presented. Simulation results for sinusoidal function approximation with various quantization levels are shown. The results indicate that the network presents good approximation capability even with severe quantization. The parameter quantization decreases the memory size and circuit complexity required to store the network parameters leading to compact mixed-signal circuits proper for low-power applications. ©2008 IEEE.
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Let (X, d) be a compact metric space and f: X → X a continuous function and consider the hyperspace (K(X), H) of all nonempty compact subsets of X endowed with the Hausdorff metric induced by d. Let f̄: K(X) → K (X) be defined by f̄(A) = {f(a)/a ∈ A} the natural extension of f to K(X), then the aim of this work is to study the dynamics of f when f is turbulent (erratic, respectively) and its relationships.
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In this paper, we propose new circuits for the implementation of Radial Basis Functions (RBF). These RBFs are obtained by the subtraction of two differential pair output currents in a folded cascode configuration. We also propose a multidimensional version based on the unidimensional circuits. SPICE simulation and experimental results indicate good functionality. These circuits are intended to be applied in the implementation of radial basis function networks. Possible applications of these networks include transducer signal conditioning and processing in onboard telemetry systems for aircraft and spacecraft vehicles. © 2010 IEEE.
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This paper presents the construction of a fuzzy environmental quality index for decision support in municipal environmental management. Five groups of indicators were selected in order to obtain an equation that best represented reality in terms of environmental quality. The calculation was carried out using fuzzy mathematical concepts, with the aid of the package Fuzzy Logical Toolbox 2.1 for Matlab ® 6.1, which provides functions and some applications of the theory of fuzzy sets. The work seeks to create a method of inference concerning the nature of urban areas that are unsustainable with respect to the environment, an issue that is often relegated to the background during public policy discussions. The development of this index, together with its implementation and dissemination, could improve public awareness of environmental issues, and promote mobilization towards the use of best practices in local development. © 2010 IEEE.
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Due to growing urbanization and industrialization, the environment is suffering from pollution of rivers, degradation of soils and deteriorated air quality. Quality indices appear to be useful to evaluate the conditions of these media. The aim of this study was the development of a water quality index using a fuzzy inference system, since such an approach has proved advantageous in addressing problems that are subjective by nature or for which the data are uncertain. The methodology employed was based on this inference system, and considered the nine water quality parameters employed by CETESB (Companhia de Tecnologia de Saneamento Ambiental, São Paulo, Brazil) to evaluate water quality. After assessment of the data using the index, a comparison was made with the WQI (Water Quality Index), which is used for the monitoring of various water bodies, including in the study region. The results obtained using the index developed on the basis of fuzzy inference were found to be more useful than those derived from the method currently used by CETESB, since losses and/or omissions concerning individual parameters were minimized. © 2010 IEEE.
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This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.
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Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Includes bibliography.