Blind multivariable ARMA subspace identification
نویسندگان
چکیده
منابع مشابه
Blind multivariable ARMA subspace identification
In this paper, we study the deterministic blind identification of multiple channel state-space models having a common unknown input using measured output signals that are perturbed by additive white noise sequences. Different from traditional blind identification problems, the considered system is an autoregressive system rather than an FIR system; hence, the concerned identification problem is...
متن کاملHOS-based orthogonal subspace algorithm for causal ARMA system identification
In this paper a new method, based on subspaces of a cumulant matrix, is proposed for the blind identi"cation of an ARMA system which is driven by white non-Gaussian noise. The relationship between the cumulants and the impulse response is exploited to arrive at a relation between a cumulant matrix and a matrix consisting of impulse responses. This will lead to the formulation of a new algorithm...
متن کاملSubspace angles between ARMA models
We de2ne a notion of subspace angles between two linear, autoregressive moving average, single-input–single-output models by considering the principal angles between subspaces that are derived from these models. We show how a recently de2ned metric for these models, which is based on their cepstra, relates to the subspace angles between the models. c © 2002 Elsevier Science B.V. All rights rese...
متن کاملSubspace Identification of Multivariable Hammerstein and Wiener Models
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 functi...
متن کاملBlind system identification using minimum noise subspace
Developing fast and robust methods for identifying multiple FIR channels driven by an unknown common source is important for wireless communications, speech reverberation cancellation, and other applications. In this correspondence, we present a new method that exploits a minimum noise subspace (MNS). The MNS is computed from a set of channel output pairs that form a “tree.” The “tree” exploits...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Automatica
سال: 2016
ISSN: 0005-1098
DOI: 10.1016/j.automatica.2015.12.005