-Stable distributions are a family of probability distributions found to be suitable to model many complex processes and phenomena in several research fields, such as medicine, physics, finance and networking, among o...
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-Stable distributions are a family of probability distributions found to be suitable to model many complex processes and phenomena in several research fields, such as medicine, physics, finance and networking, among others. However, the lack of closed expressions makes their evaluation analytically intractable, and alternative approaches are computationally expensive. Existing numerical programs are not fast enough for certain applications and do not make use of the parallel power of general purpose graphic processing units. In this paper, we develop novel parallel algorithms for the probability density function and cumulative distribution function-including a parallel Gauss-Kronrod quadrature-, quantile function, random number generator and maximum likelihood estimation of -stable distributions using OpenCL, achieving significant speedups and precision in all cases. Thanks to the use of OpenCL, we also evaluate the results of our library with different GPU architectures.
This paper presents a comparison of results of coherent and incoherent sampling measurements of complex ratios of sinusoidal voltages, obtained with the use of an ellipse-fitting algorithm (EFA) and with the use of di...
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This paper presents a comparison of results of coherent and incoherent sampling measurements of complex ratios of sinusoidal voltages, obtained with the use of an ellipse-fitting algorithm (EFA) and with the use of discrete Fourier transform (DFT). The EFA algorithm has not been yet used in the measurements of the complex voltage ratio. Known applications of EFA in impedance measurements were based on simultaneous sampling of two voltages by a two-channel aquisition card. Measurements presented in this paper were made with an automated measurement system consisting of Keysight 3458A multimeter operating in the DC voltage sampling mode. The internal 20-MHz clock generator of this multimeter was replaced with a custom-made clock module dividing the clock frequency by 2 and providing fiber optic 10-MHz synchronization signal. This signal was used as the reference frequency of the Keysight 33250A generator which served as a reference frequency clock for the dual-channel source of digitally synthesized sinusoidal voltage. Because the output frequency of the Keysight 33250A generator can be adjusted with very high resolution and accuracy, it was possible to perform coherent and incoherent sampling measurements with controlled frequency deviation.
The article presents a modified sine-fitting algorithms which can be used for high-accuracy sampling measurements of complex voltage ratio of sinusoidal signals. The proposed algorithms provide a significant reduction...
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The article presents a modified sine-fitting algorithms which can be used for high-accuracy sampling measurements of complex voltage ratio of sinusoidal signals. The proposed algorithms provide a significant reduction in the measurement uncertainty of phase shift when synchronizing the sampler and signal source is impossible.
Two approaches to moment matching based model reduction of aperiodically sampled data systems are given. In certain cases, such systems can be represented by discrete-time linear switched (LS) state space (SS) models....
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This paper addresses the quality of the solutions provided by Lyapunov-Metzler inequalities to Discrete Switched System Control. It proposes a method based on the value iteration algorithm, which is able to efficientl...
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This paper addresses the quality of the solutions provided by Lyapunov-Metzler inequalities to Discrete Switched System Control. It proposes a method based on the value iteration algorithm, which is able to efficientl...
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This paper addresses the quality of the solutions provided by Lyapunov-Metzler inequalities to Discrete Switched System Control. It proposes a method based on the value iteration algorithm, which is able to efficiently compute an approximately optimal solution to the dynamic programming formulation arising from these systems. A large number of numerical simulations are performed in order to evaluate the results. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Two iterative algorithms for solving systems of linear and nonlinear equations are proposed. For linear problems the algorithm is based on a control theoretic approach and it is guaranteed to yield a converging sequen...
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Two iterative algorithms for solving systems of linear and nonlinear equations are proposed. For linear problems the algorithm is based on a control theoretic approach and it is guaranteed to yield a converging sequence for any initial condition provided a solution exists. Systems of nonlinear equations are then considered and a generalised algorithm, again taking inspiration from control theory, is proposed. Local convergence is guaranteed in the nonlinear setting. Both the linear and the nonlinear algorithms are demonstrated on a series of numerical examples. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
New software applications for linear multivariable system identification are presented. The incorporated algorithms use subspace-based techniques (MOESP, N4SID, or their combination) to find a standard discrete-time s...
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ISBN:
(纸本)9781538638422
New software applications for linear multivariable system identification are presented. The incorporated algorithms use subspace-based techniques (MOESP, N4SID, or their combination) to find a standard discrete-time state-space description, and optionally the covariance matrices and Kalman predictor gain, using input and output (I/O) trajectories. For flexibility, separate applications are offered for obtaining the processed triangular factor of the structured, block-Hankel-block matrix of I/O data (using fast or standard QR factorization algorithms), for computing the system and predictor matrices, for estimating the initial state of the system, and for simulating and evaluating the model. The applications are encapsulated in Docker containers, which are managed by the Kubernetes platform on a Linux machine. This ensures greater flexibility, enhanced security, and fast execution. The services to be implemented are part of a cloud-based open platform for process control applications.
Two approaches to moment matching based model reduction of aperiodically sampled data systems are given. In certain cases, such systems can be represented by discrete time linear switched (LS) state space (SS) models....
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Two approaches to moment matching based model reduction of aperiodically sampled data systems are given. In certain cases, such systems can be represented by discrete time linear switched (LS) state space (SS) models. One of the approaches investigated in the paper is to apply model reduction by moment matching on the linear time-invariant (LTI) plant model, then compare the responses of the LS SS models acquired from the original and reduced order LTI plants. The second approach is to apply a moment matching based model reduction method on the LS SS model acquired from the original LTI plant;and then compare the responses of the original and reduced LS SS models. It is proven that for both methods, as long as the original LTI plant is stable, the resulting reduced order LS SS model of the sampled data system is quadratically stable. The results from two approaches are compared with numerical examples. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Two iterative algorithms for solving systems of linear and nonlinear equations are proposed. For linear problems the algorithm is based on a control theoretic approach and it is guaranteed to yield a converging sequen...
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