988 resultados para continuous nonlinear programming
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The commercial data acquisition systems used for seismic exploration are usually expensive equipment. In this work, a low cost data acquisition system (Geophonino) has been developed for recording seismic signals from a vertical geophone. The signal goes first through an instrumentation amplifier, INA155, which is suitable for low amplitude signals like the seismic noise, and an anti-aliasing filter based on the MAX7404 switched-capacitor filter. After that, the amplified and filtered signal is digitized and processed by Arduino Due and registered in an SD memory card. Geophonino is configured for continuous registering, where the sampling frequency, the amplitude gain and the registering time are user-defined. The complete prototype is an open source and open hardware system. It has been tested by comparing the registered signals with the ones obtained through different commercial data recording systems and different kind of geophones. The obtained results show good correlation between the tested measurements, presenting Geophonino as a low-cost alternative system for seismic data recording.
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The contributions of the concrete slab and composite action to the vertical shear strength of continuous steel-concrete composite beams are ignored in current design codes, which result in conservative designs. This paper investigates the ultimate strength of continuous composite beams in combined bending and shear by using the finite element analysis method. A three-dimensional finite element model has been developed to account for the geometric and material nonlinear behaviour of continuous composite beams. The finite element model is verified by experimental results and then used to study the effects of the concrete slab and shear connection on the vertical shear strength. The moment-shear interaction strength of continuous composite beams is also investigated by varying the moment/ shear ratio. It is shown that the concrete slab and composite action significantly increase the ultimate strength of continuous composite beams. Based on numerical results, design models are proposed for the vertical shear strength and moment-shear interaction of continuous composite beams. The proposed design models, which incorporates the effects of the concrete slab, composite action, stud pullout failure and web shear buckling, are compared with experimental results with good agreement. (C) 2003 Elsevier Ltd. All rights reserved.
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We show that the intracavity Kerr nonlinear coupler is a potential source of bright continuous variable entangled light beams which are tunable and spatially separated. We use a linearized fluctuation analysis to calculate the necessary correlations in regimes where it is valid. This means that we are treating regimes where the system exhibits Gaussian statistics so that well-known criteria are both necessary and sufficient to demonstrate entanglement. This system may be realized with integrated optics and thus provides a potentially rugged and stable source of bright entangled beams.
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Aim To develop an appropriate dosing strategy for continuous intravenous infusions (CII) of enoxaparin by minimizing the percentage of steady-state anti-Xa concentration (C-ss) outside the therapeutic range of 0.5-1.2 IU ml(-1). Methods A nonlinear mixed effects model was developed with NONMEM (R) for 48 adult patients who received CII of enoxaparin with infusion durations that ranged from 8 to 894 h at rates between 100 and 1600 IU h(-1). Three hundred and sixty-three anti-Xa concentration measurements were available from patients who received CII. These were combined with 309 anti-Xa concentrations from 35 patients who received subcutaneous enoxaparin. The effects of age, body size, height, sex, creatinine clearance (CrCL) and patient location [intensive care unit (ICU) or general medical unit] on pharmacokinetic (PK) parameters were evaluated. Monte Carlo simulations were used to (i) evaluate covariate effects on C-ss and (ii) compare the impact of different infusion rates on predicted C-ss. The best dose was selected based on the highest probability that the C-ss achieved would lie within the therapeutic range. Results A two-compartment linear model with additive and proportional residual error for general medical unit patients and only a proportional error for patients in ICU provided the best description of the data. Both CrCL and weight were found to affect significantly clearance and volume of distribution of the central compartment, respectively. Simulations suggested that the best doses for patients in the ICU setting were 50 IU kg(-1) per 12 h (4.2 IU kg(-1) h(-1)) if CrCL < 30 ml min(-1); 60 IU kg(-1) per 12 h (5.0 IU kg(-1) h(-1)) if CrCL was 30-50 ml min(-1); and 70 IU kg(-1) per 12 h (5.8 IU kg(-1) h(-1)) if CrCL > 50 ml min(-1). The best doses for patients in the general medical unit were 60 IU kg(-1) per 12 h (5.0 IU kg(-1) h(-1)) if CrCL < 30 ml min(-1); 70 IU kg(-1) per 12 h (5.8 IU kg(-1) h(-1)) if CrCL was 30-50 ml min(-1); and 100 IU kg(-1) per 12 h (8.3 IU kg(-1) h(-1)) if CrCL > 50 ml min(-1). These best doses were selected based on providing the lowest equal probability of either being above or below the therapeutic range and the highest probability that the C-ss achieved would lie within the therapeutic range. Conclusion The dose of enoxaparin should be individualized to the patients' renal function and weight. There is some evidence to support slightly lower doses of CII enoxaparin in patients in the ICU setting.
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We describe a generalization of the cluster-state model of quantum computation to continuous-variable systems, along with a proposal for an optical implementation using squeezed-light sources, linear optics, and homodyne detection. For universal quantum computation, a nonlinear element is required. This can be satisfied by adding to the toolbox any single-mode non-Gaussian measurement, while the initial cluster state itself remains Gaussian. Homodyne detection alone suffices to perform an arbitrary multimode Gaussian transformation via the cluster state. We also propose an experiment to demonstrate cluster-based error reduction when implementing Gaussian operations.
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In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the cross-entropy method in the context of continuous optimization. We demonstrate the effectiveness of the cross-entropy method for solving difficult continuous multi-extremal optimization problems, including those with non-linear constraints.
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We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.
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This work introduces a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. Convergence of the output error for the proposed control method is verified by using a Lyapunov function. Several simulation examples are provided to demonstrate the efficiency of the developed control method. The manner in which such a method is extended to nonlinear multi-variable systems with different delays between the input-output pairs is considered and demonstrated through simulation examples.
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We have proposed and demonstrated a nonlinear polarization-rotation-based fiber laser with two different operation states: passive mode-locking and multiwavelength emission. The intensity-dependent transmission or loss induced by nonlinear polarization rotation accounts for the distinct operation regimes. Our experiment results indicate that both passively mode-locked pulses and continuous-wave multiwavelength can be generated from the same fiber laser just through adjusting polarizations. Another characteristic of the current multiwavelength laser is that the used periodic filter is a birefringence fiber filter, which facilitates all-fiber integration of the fiber laser, so it is a potential multifunction laser source with all-fiber configuration and convenient manipulation. © 2008 IEEE.
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We have proposed and demonstrated a nonlinear polarization-rotation-based fiber laser with two different operation states: passive mode-locking and multiwavelength emission. The intensity-dependent transmission or loss induced by nonlinear polarization rotation accounts for the distinct operation regimes. Our experiment results indicate that both passively mode-locked pulses and continuous-wave multiwavelength can be generated from the same fiber laser just through adjusting polarizations. Another characteristic of the current multiwavelength laser is that the used periodic filter is a birefringence fiber filter, which facilitates all-fiber integration of the fiber laser, so it is a potential multifunction laser source with all-fiber configuration and convenient manipulation. © 2008 IEEE.
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Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.
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We demonstrate light pulse combining and pulse compression using a continuous-discrete nonlinear system implemented in a multi-core fiber (MCF). It is shown that the pulses initially injected into all of the cores of a ring MCF are combined by nonlinearity into a small number of cores with simultaneous pulse compression. We demonstrate the combining of 77% of the energy into one core with pulse compression over 14× in a 20-core MCF. We also demonstrate that a suggested scheme is insensitive to the phase perturbations. Nonlinear spatio-temporal pulse manipulation in multi-core fibers can be exploited for various applications, including pulse compression, switching, and combining.
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In linear communication channels, spectral components (modes) defined by the Fourier transform of the signal propagate without interactions with each other. In certain nonlinear channels, such as the one modelled by the classical nonlinear Schrödinger equation, there are nonlinear modes (nonlinear signal spectrum) that also propagate without interacting with each other and without corresponding nonlinear cross talk, effectively, in a linear manner. Here, we describe in a constructive way how to introduce such nonlinear modes for a given input signal. We investigate the performance of the nonlinear inverse synthesis (NIS) method, in which the information is encoded directly onto the continuous part of the nonlinear signal spectrum. This transmission technique, combined with the appropriate distributed Raman amplification, can provide an effective eigenvalue division multiplexing with high spectral efficiency, thanks to highly suppressed channel cross talk. The proposed NIS approach can be integrated with any modulation formats. Here, we demonstrate numerically the feasibility of merging the NIS technique in a burst mode with high spectral efficiency methods, such as orthogonal frequency division multiplexing and Nyquist pulse shaping with advanced modulation formats (e.g., QPSK, 16QAM, and 64QAM), showing a performance improvement up to 4.5 dB, which is comparable to results achievable with multi-step per span digital back propagation.
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The nonlinear inverse synthesis (NIS) method, in which information is encoded directly onto the continuous part of the nonlinear signal spectrum, has been proposed recently as a promising digital signal processing technique for combating fiber nonlinearity impairments. However, because the NIS method is based on the integrability property of the lossless nonlinear Schrödinger equation, the original approach can only be applied directly to optical links with ideal distributed Raman amplification. In this paper, we propose and assess a modified scheme of the NIS method, which can be used effectively in standard optical links with lumped amplifiers, such as, erbium-doped fiber amplifiers (EDFAs). The proposed scheme takes into account the average effect of the fiber loss to obtain an integrable model (lossless path-averaged model) to which the NIS technique is applicable. We found that the error between lossless pathaveraged and lossy models increases linearly with transmission distance and input power (measured in dB). We numerically demonstrate the feasibility of the proposed NIS scheme in a burst mode with orthogonal frequency division multiplexing (OFDM) transmission scheme with advanced modulation formats (e.g., QPSK, 16QAM, and 64QAM), showing a performance improvement up to 3.5 dB; these results are comparable to those achievable with multi-step per span digital backpropagation.