Results 11 to 20 of about 2,984,455 (293)
An iterative algorithm for Hamiltonian identification of quantum systems
2016 IEEE 55th Conference on Decision and Control (CDC), 2016 Identifying parameters in the system Hamiltonian is a vitally important task in the development of quantum technology. This paper investigates the problem of Hamiltonian identification for closed quantum systems and develops a new algorithm to achieve the task of identifying the Hamiltonian.
Wang, Y, Qi, B, Dong, D, Petersen, IR
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Iterative procedures for identification of nonlinear interconnected systems [PDF]
, 2007 This work addresses the identification problem of a discrete-time nonlinear system composed by linear and nonlinear subsystems. Systems in this class will be represented by Linear Fractional Transformations.
Date, P, Pepona, E
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Convergence analysis of iterative identification and optimization schemes [PDF]
Proceedings of the 2003 American Control Conference, 2003., 2004 The use of measurements to compensate for model uncertainty has received increasing attention in the context of process optimization. The idea consists of iteratively using the measurements for identifying model parameters and the updated model for optimization.
Srinivasan, B., Bonvin, D.
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Seeded iterative clustering for histology region identification
CoRR, 2022 Annotations are necessary to develop computer vision algorithms for histopathology, but dense annotations at a high resolution are often time-consuming to make. Deep learning models for segmentation are a way to alleviate the process, but require large amounts of training data, training times and computing power.
Eduard Chelebian +2 more
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Algorithms, 2016 This paper discusses the parameter estimation problems of multi-input output-error autoregressive (OEAR) systems. By combining the auxiliary model identification idea and the data filtering technique, a data filtering based recursive generalized least ...
Jiling Ding
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Mathematics, 2022 For multi-phase batch processes with different dimensions whose dynamics can be described as a linear discrete-time-invariant system in each phase, a data-driven optimal ILC was explored using multi-operation input and output data that subordinate a ...
Yan Geng, Shouqin Wang, Xiaoe Ruan
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Automatic species identification of live moths [PDF]
, 2007 A collection consisting of the images of 774 live moth individuals, each moth belonging to one of 35 different UK species, was analysed to determine if data mining techniques could be used effectively for automatic species identification. Feature vectors
Watson, Anna T., Mayo, Michael
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Mathematics, 2019 This paper is concerned with the identification problem for multivariable equation-error systems whose disturbance is an autoregressive moving average process. By means of the hierarchical identification principle and the iterative search, a hierarchical
Lijuan Wan +3 more
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Fast iterative solvers for PDE-constrained optimization problems [PDF]
, 2013 In this thesis, we develop preconditioned iterative methods for the solution of matrix systems arising from PDE-constrained optimization problems. In order to do this, we exploit saddle point theory, as this is the form of the matrix systems we wish to ...
Pearson, John W
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A novel Fourier-based deconvolution algorithm with improved efficiency and convergence
Journal of Low Frequency Noise, Vibration and Active Control, 2020 Various deconvolution algorithms for acoustic source are developed to improve spatial resolution and suppress sidelobe of the conventional beamforming. To improve the computational efficiency and solution convergence of deconvolution, this paper proposes
Linbang Shen +3 more
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