The concentration and sparsity of signal representation in the Hermite transform (HT) basis may highly depend on a properly chosen scaling factor and discrete time shift parameter. In that sense, we propose a simple a...
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The concentration and sparsity of signal representation in the Hermite transform (HT) basis may highly depend on a properly chosen scaling factor and discrete time shift parameter. In that sense, we propose a simple and efficient iterative procedure for automatic determination of the optimal scaling factor. The optimization criterion is based on the l(1)-norm acting as a measure of signal concentration in the HT domain. Instead of centering the signal at the zero time instant, we also propose to shift the center for a few points left or right, which will additionally improve the concentration. An important application of the proposed optimization approach is the compression of QRS complexes, where properly chosen scaling factor and time-shift increase the compression performance. The results are verified using synthetic and real examples and compared with the existing approach for the compression of QRS complexes. (C) 2016 Elsevier B.V. All rights reserved.
In nuclear magnetic resonance (NMR) quantum computation, the selective control of multiple homonuclear spins is usually slow because their resonance frequencies are very close to each other. To quickly implement the c...
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In nuclear magnetic resonance (NMR) quantum computation, the selective control of multiple homonuclear spins is usually slow because their resonance frequencies are very close to each other. To quickly implement the controls against decoherence effects, this brief presents an efficient numerical algorithm for designing minimum-time local transformations in two homonuclear spins. We obtain an accurate minimum-time estimation via geometric analysis on the two-timescale decomposition of the dynamics. Such estimation narrows down the range of search for the minimum-time control with a gradient-type optimization algorithm. Numerical simulations show that this method can remarkably reduce the search efforts, especially when the frequency difference is very small and the control field is high. Its effectiveness is further demonstrated by NMR experiments with two homunuclear carbon spins in a trichloroethylene (C2H1Cl3) sample system.
Parameter estimation is important for controller design of linear systems and nonlinear systems. The parameters of the systems can be estimated through some identification algorithms. This paper presents a recursive g...
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Parameter estimation is important for controller design of linear systems and nonlinear systems. The parameters of the systems can be estimated through some identification algorithms. This paper presents a recursive generalized extended least squares algorithm and a generalized extended stochastic gradient (GESG) algorithm for identifying the parameters of a class of nonlinear systems. Furthermore, a multi-innovation GESG algorithm is derived to improve the estimation accuracy. The simulation example is provided to test the effectiveness of the proposed algorithms.
This paper investigates the drag minimization in a two-dimensional flow which is governed by a nonhomogeneous Navier-Stokes equations. Two approaches are utilized to derive shape gradient of the cost functional. The f...
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This paper investigates the drag minimization in a two-dimensional flow which is governed by a nonhomogeneous Navier-Stokes equations. Two approaches are utilized to derive shape gradient of the cost functional. The first one is to use the shape derivative of the fluid state and its associated adjoint state;the second one is to utilize the differentiability of a minimax formulation involving a Lagrange functional with a function space parametrization technique. Finally, a gradient type algorithm is effectively formulated and implemented for the mentioned drag minimization problem. (C) 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 25: 1149-1166, 2009
This paper investigates shape optimization of a solid body located in Navier-Stokes flow in two dimensions. The minimization problem of total dissipated energy is established in the fluid domain. The discretization of...
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This paper investigates shape optimization of a solid body located in Navier-Stokes flow in two dimensions. The minimization problem of total dissipated energy is established in the fluid domain. The discretization of Navier-Stokes equations is accomplished using a new stabilized finite element method which does not need a stabilization parameter or calculation of high order derivatives. We derive the structures of discrete Eulerian derivative of the cost functional by a discrete adjoint method with a function space parametrization technique. A gradient type optimization algorithm with a mesh adaptation technique and a mesh moving strategy is effectively formulated and implemented. (C) 2010 Published by Elsevier B.V. on behalf of IMACS.
We propose an adaptive notch filter that realizes the phase shift of the all-pass filter by the expression of Fourier sine series. The method of controlling the weights of the all-pass filter formed by IIR filters is ...
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We propose an adaptive notch filter that realizes the phase shift of the all-pass filter by the expression of Fourier sine series. The method of controlling the weights of the all-pass filter formed by IIR filters is well known. However, these adaptive notch filters have not been put to practical use due to the peculiar stability problems of IIR filters and the problem of determining the degree of the IIR filter. The proposed adaptive notch filter is always stable since the all-pass filter is formed by exponential filters. Furthermore, the adaptive algorithm is a simple gradient-based algorithm and convergence of weights is guaranteed. The degree of the all-pass filter depends only on the required steepness of the elimination characteristic and does not depend on the number of narrowband signals that are to be eliminated. Furthermore, the proposed method is suitable for practical use because the elimination characteristic is hardly influenced by a broadband signal added to the narrowband signal. The analytical results and a rigorous verification of the above features by computer simulation are presented. (C) 2010 Wiley Periodicals, Inc. Electron Comm Jpn, 93(5): 8-14, 2010;Published online in Wiley Inter Science (***). DOI 10.1002/ecj.10256
A continuation of previous authors' work on adaptive parameter estimation for linear dynamical systems having irrational transfer function is presented in this work. An original modification of the gradient algori...
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A continuation of previous authors' work on adaptive parameter estimation for linear dynamical systems having irrational transfer function is presented in this work. An original modification of the gradient algorithm, inspired by the variable structure control techniques and additionally featuring a time-varying adaptation gain, is presented and analyzed using Lyapunov techniques. The exposition is illustrated by several numerical examples which illustrate the effectiveness of the proposed algorithm. (C) 2019 Published by Elsevier B.V. on behalf of IMACS.
In recent years, extreme learning machine (ELM) and its improved algorithms have been successfully applied to various classification and regression tasks. In these algorithms, MSE criterion is commonly used to control...
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In recent years, extreme learning machine (ELM) and its improved algorithms have been successfully applied to various classification and regression tasks. In these algorithms, MSE criterion is commonly used to control training error. However, MSE criterion is not suitable to deal with outliers, which can exist in general regression or classification tasks. In this paper, a novel extreme learning machine under minimum information divergence criterion (ELM-MinID) is proposed to deal with the training set with noises. In minimum information divergence criterion, the Gaussian kernel function and Euclidean information divergence are utilized to substitute the mean square error (MSE) criterion to enhance the anti-noise ability of ELM. Experimental results on two synthetic datasets and eleven benchmark datasets show that this method is superior to traditional ELMs.
In this paper, we study the coordination between biogas producers who can use the biogas themselves, exchange biogas with their neighbors, or deliver it to the various energy grids, such as the low pressure gas grid o...
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In this paper, we study the coordination between biogas producers who can use the biogas themselves, exchange biogas with their neighbors, or deliver it to the various energy grids, such as the low pressure gas grid or the power grid. These producers are called prosumers. In this setting, gas storage, fuel cells, microcombined heat power systems, and heat buffers are all part of the prosumers' node. We aim to optimize the imbalance, profit, and comfort levels per prosumer, while taking the constraints of the energy grids into account and while allowing prosumers to exchange energy with each other. This results in a two-layer optimization problem formulation. In addition, in practice, the communication between prosumers among each other and with grid operators is done in an asynchronous manner. In this paper, we study the problem of two-layer optimization for biogas prosumers embedded in multiple energy grids, while the (bidirectional) communication between the various partners is done asynchronously. We prove the convergence of the asynchronous coordination algorithm that uses both the inputs and the states. We conduct simulations for the biogas prosumer setting, using realistic data to illustrate the convergence of the algorithm and to study its practical implementation.
This paper is concerned with a shape, sensitivity analysis of a viscous incompressible fluid driven by Stokes equations. The structures of continuous shape gradients with respect to the shape of the variable domain fo...
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This paper is concerned with a shape, sensitivity analysis of a viscous incompressible fluid driven by Stokes equations. The structures of continuous shape gradients with respect to the shape of the variable domain for some given cost functionals are established by introducing the Piola transformation and then deriving the state derivative and its associated adjoint state. Finally we give the finite element approximation of the problem and a gradient type algorithm is effectively used for our problem. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.
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