Results 1 to 10 of about 3,247,690 (230)
Machines, 2022 With the continuous development of large-scale aluminum reduction cells, the problem of the uniform distribution of alumina concentration in the cell has become more and more serious for the reduction process. In order to achieve the uniform distribution
Jiarui Cui +6 more
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Subspace System Identification via Weighted Nuclear Norm Optimization
, 2012 We present a subspace system identification method based on weighted nuclear norm approximation. The weight matrices used in the nuclear norm minimization are the same weights as used in standard subspace identification methods.
Hansson, Anders +2 more
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Subspace identification of switching model [PDF]
IFAC Proceedings Volumes, 2003 Subspace identication of switching model is considered in this paper. Here the switching model is supposed to be a sum of weighted linear models. The method established uses recursive subspace identification to estimate the switching function and least squares method for local model Markov parameters estimation.
Pekpe, Komi +3 more
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Energies, 2022 This paper aims to address a finite-horizon model predictive control (MPC) for non-linear drum-type boiler-turbine system using a system-identification method.
Jun Wang, Baocang Ding, Ping Wang
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Structure-Based Subspace Method for Multi-Channel Blind System Identification
, 2017 In this work, a novel subspace-based method for blind identification of multichannel finite impulse response (FIR) systems is presented. Here, we exploit directly the impeded Toeplitz channel structure in the signal linear model to build a quadratic form
Abed-Meraim, Karim +2 more
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Recursive Nuclear Norm based Subspace Identification
IFAC-PapersOnLine, 2017 Abstract Nuclear norm based subspace identification methods have recently gained importance due to their ability to find low rank solutions while maintaining accuracy through convex optimization. However, their heavy computational burden typically precludes the use in an online, recursive manner, such as may be required for adaptive control.
Telsang, B. (author) +2 more
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Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms [PDF]
Journal of Advances in Computer Engineering and Technology, 2015 Neural networks are applicable in identification systems from input-output data. In this report, we analyze theHammerstein-Wiener models and identify them.
Maryam Ashtari Mahini +2 more
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Subspace-Based Blind Channel Identification for Cyclic Prefix Systems Using Few Received Blocks [PDF]
, 2007 In this paper, a novel generalization of subspace-based blind channel identification methods in cyclic prefix (CP) systems is proposed. For the generalization, a new system parameter called repetition index is introduced whose value is unity for ...
Su, Borching, Vaidyanathan, P. P.
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Bilinear System Identification Using Subspace Method
مجلة بغداد للعلوم, 2007 In this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white .
Baghdad Science Journal
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