A new subspace method for the blind identification of infinite impulse response (IIR), single input-multiple output (SIMO) systems represented using orthonormal bases with fixed poles, is presented in this paper. Basi...
详细信息
A new subspace method for the blind identification of infinite impulse response (IIR), single input-multiple output (SIMO) systems represented using orthonormal bases with fixed poles, is presented in this paper. Basis coefficients are estimated in closed form, up to a scalar factor, by first computing the column space of the output Hankel matrix using singular value decomposition (SVD), and then solving a least squares problem also resorting to an SVD. The performance of the proposed algorithm is illustrated through a simulation example.
In this paper, subspace-based algorithms for the simultaneous identification of the linear and nonlinear parts of multivariable Hammerstein and Wiener models are presented. The proposed algorithms consist basically of...
详细信息
In this paper, subspace-based algorithms for the simultaneous identification of the linear and nonlinear parts of multivariable Hammerstein and Wiener models are presented. The proposed algorithms consist basically of...
详细信息
In this paper, subspace-based algorithms for the simultaneous identification of the linear and nonlinear parts of multivariable Hammerstein and Wiener models are presented. The proposed algorithms consist basically of two steps. The first one is a standard (linear) subspace algorithm applied to an equivalent linear system whose inputs (respectively outputs) are filtered (by the nonlinear functions describing the static nonlinearities) versions of the original inputs (respectively outputs). The second step consists in a 2-norm minimization problem which is solved via a Singular Value Decomposition.
暂无评论