| Pal D. Balanced Stochastic Realization and Model Reduction. Master's thesis, Whasington State University, Electrical Engineering, 1982. |
....we introduce the notation used throughout the paper : input and output block Hankel matrices, system related matrices and weighting matrices. We also shortly revise some results on subspace identification. Throughout the paper, we will consider the model (1) 2) in its forward innovations form as [6] : x k 1 = Ax k Bu k Ee k ; y k = Cx k Du k Fe k ; E[e k e T l ] I ffi kl ; 3) with E 2 R n Thetal , F 2 R l Thetal , and the innovations e k 2 R l uncorrelated with u k . The transformation from the system (1) 2) to this innovations model can be done through the solution of a ....
....k Bu k Ee k ; y k = Cx k Du k Fe k ; E[e k e T l ] I ffi kl ; 3) with E 2 R n Thetal , F 2 R l Thetal , and the innovations e k 2 R l uncorrelated with u k . The transformation from the system (1) 2) to this innovations model can be done through the solution of a Riccati equation [6]. The steady state Kalman gain is given by K = EF Gamma1 2 R n Thetal . Subspace identification algorithms make extensive use of input and output block Hankel matrices. We define : U p def = 0 B B B B B u 0 u 1 : u j Gamma1 u 1 u 2 : u j : u i Gamma1 u i ....
Pal D. (1982). Balanced Stochastic Realization and Model Reduction. Master's thesis, Washington State University, Electrical Engineering.
No context found.
Pal D. Balanced Stochastic Realization and Model Reduction. Master's thesis, Whasington State University, Electrical Engineering, 1982.
No context found.
Pal D. (1982). Balanced Stochastic Realization and Model Reduction. Master's thesis, Washington State University, Electrical Engineering.
No context found.
Pal D. (1982). Balanced Stochastic Realization and Model Reduction. Master's thesis, Washington State University, Electrical Engineering.
No context found.
Pal D. Balanced Stochastic Realization and Model Reduction. Master 's thesis, Whasington State University, Electrical Engineering, 1982.
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