- 1999 () Citation Context ...n effective and systematic solution to the circuit-level system simulation problem within the framework of piecewise harmonic-balance (HB) methods based on Krylov-subspace model or
Since the developed method stays close the his LTI counterpart it is intuitive and easy to use, this contradictory to methods which rely on support vector machines. The effectiveness of the approach was illustrated with a simple simulation example....
The algorithm implements the N4SID, PO-MOESP and CCA methods, which are well known in the literature on 1D system identification, but here we do so for the 2D CRSD Roesser model. The algorithm solves the 2D system identification problem by maintaining the constraint structure imposed by the ...
9.Subspace Method for System Identification and Its Application to Complicated Structures子空间系统辨识方法及其在复杂结构中的应用 10.Subspace Methods for System Identification and Predictive Control Design;基于子空间方法的系统辨识及预测控制设计 11.The Research of the Closed-loop Identification of Thermal ...
The simulation of electronic circuits involves the numerical solution of very large-scale, sparse, in general nonlinear, systems of differential-algebraic ... RW Freund - 《Journal of Computational & Applied Mathematics》 被引量: 531发表: 2000年 Model Reduction Methods Based on Krylov Subspaces SIM...
Methods Simulations and fidelity calculations. Gate operations on CQ and CD qubits were simulated using standard numerical techniques to solve i' r_ ¼½H; r, where r is the 2D (3D) density matrix for the CD (CQ) qubit, defined by Hamiltonian H ¼ HCD (HCQ). For the ...
Journal of System Simulation., 19 (17) (2007), pp. 3855-3873 View in ScopusGoogle Scholar Yu, 2012 Yu J. Online quality prediction of nonlinear and non-Gaussian chemical processes with shifting dynamics using finite mixture model based Gaussian process regression approach Chemical Engineering Scienc...
The second step consists of a 2-norm minimization problem which is solved via Singular Value Decomposition. Consistency of the estimates can be guaranteed under weak assumptions. The performance of the proposed identification algorithms is illustrated through simulation examples....
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Actually, industrial processes have large amounts of operating data which contain abundant information about the system. Subspace model identification which uses process data to identify system models comes into being under this kind of background. There are several methods of subspace algorithms, such...