820 resultados para Lanczos, Linear systems, Generalized cross validation
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar.
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This paper presents necessary and sufficient conditions for the following problem: given a linear time invariant plant G(s) = N(s)D(s)-1 = C(sI - A]-1B, with m inputs, p outputs, p > m, rank(C) = p, rank(B) = rank(CB) = m, £nd a tandem dynamic controller Gc(s) = D c(s)-1Nc(s) = Cc(sI - A c)-1Bc + Dc, with p inputs and m outputs and a constant output feedback matrix Ko ε ℝm×p such that the feedback system is Strictly Positive Real (SPR). It is shown that this problem has solution if and only if all transmission zeros of the plant have negative real parts. When there exists solution, the proposed method firstly obtains Gc(s) in order to all transmission zeros of Gc(s)G(s) present negative real parts and then Ko is found as the solution of some Linear Matrix Inequalities (LMIs). Then, taking into account this result, a new LMI based design for output Variable Structure Control (VSC) of uncertain dynamic plants is presented. The method can consider the following design specifications: matched disturbances or nonlinearities of the plant, output constraints, decay rate and matched and nonmatched plant uncertainties. © 2006 IEEE.
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This paper discusses the dynamic behaviour of a nonlinear two degree-of-freedom system consisting of a harmonically excited linear oscillator weakly connected to a nonlinear attachment that behaves as a hardening Duffing oscillator. A system which behaves in this way could be a shaker (linear system) driving a nonlinear isolator. The mass of the nonlinear system is taken to be much less than that in the linear system and thus the nonlinear system has little effect on the dynamics of the linear system. Of particular interest is the situation when the linear natural frequency of the nonlinear system is less than the natural frequency of the linear system such that the frequency response curve of the nonlinear system bends to higher frequencies and thus interacts with the resonance frequency of the linear system. It is shown that for some values of the system parameters a complicated frequency response curve for the nonlinear system can occur; closed detached curves can appear as a part of the overall amplitude-frequency response. The reason why these detached curves appear is presented and approximate analytical expressions for the jump-up and jump-down frequencies of the system under investigation are given.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Ciência do Solo) - FCAV
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Genética e Melhoramento Animal - FCAV
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The education designed and planned in a clear and objective manner is of paramount importance for universities to prepare competent professionals for the labor market, and above all can serve the population with an efficient work. Specifically, in relation to engineering, conducting classes in the laboratories it is very important for the application of theory and development of the practical part of the student. The planning and preparation of laboratories, as well as laboratory equipment and activities should be developed in a succinct and clear way, showing to students how to apply in practice what has been learned in theory and often shows them why and where it can be used when they become engineers. This work uses the MATLAB together with the System Identification Toolbox and Arduino for the identification of linear systems in Linear Control Lab. MATLAB is a widely used program in the engineering area for numerical computation, signal processing, graphing, system identification, among other functions. Thus the introduction to MATLAB and consequently the identification of systems using the System Identification Toolbox becomes relevant in the formation of students to thereafter when necessary to identify a system the base and the concept has been seen. For this procedure the open source platform Arduino was used as a data acquisition board being the same also introduced to the student, offering them a range of software and hardware for learning, giving you every day more luggage to their training
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The education designed and planned in a clear and objective manner is of paramount importance for universities to prepare competent professionals for the labor market, and above all can serve the population with an efficient work. Specifically, in relation to engineering, conducting classes in the laboratories it is very important for the application of theory and development of the practical part of the student. The planning and preparation of laboratories, as well as laboratory equipment and activities should be developed in a succinct and clear way, showing to students how to apply in practice what has been learned in theory and often shows them why and where it can be used when they become engineers. This work uses the MATLAB together with the System Identification Toolbox and Arduino for the identification of linear systems in Linear Control Lab. MATLAB is a widely used program in the engineering area for numerical computation, signal processing, graphing, system identification, among other functions. Thus the introduction to MATLAB and consequently the identification of systems using the System Identification Toolbox becomes relevant in the formation of students to thereafter when necessary to identify a system the base and the concept has been seen. For this procedure the open source platform Arduino was used as a data acquisition board being the same also introduced to the student, offering them a range of software and hardware for learning, giving you every day more luggage to their training
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The modern GPUs are well suited for intensive computational tasks and massive parallel computation. Sparse matrix multiplication and linear triangular solver are the most important and heavily used kernels in scientific computation, and several challenges in developing a high performance kernel with the two modules is investigated. The main interest it to solve linear systems derived from the elliptic equations with triangular elements. The resulting linear system has a symmetric positive definite matrix. The sparse matrix is stored in the compressed sparse row (CSR) format. It is proposed a CUDA algorithm to execute the matrix vector multiplication using directly the CSR format. A dependence tree algorithm is used to determine which variables the linear triangular solver can determine in parallel. To increase the number of the parallel threads, a coloring graph algorithm is implemented to reorder the mesh numbering in a pre-processing phase. The proposed method is compared with parallel and serial available libraries. The results show that the proposed method improves the computation cost of the matrix vector multiplication. The pre-processing associated with the triangular solver needs to be executed just once in the proposed method. The conjugate gradient method was implemented and showed similar convergence rate for all the compared methods. The proposed method showed significant smaller execution time.