Title :
Stability of multivariable least-squares models
Author :
Regalia, Phillip A. ; Stoica, Petre
Author_Institution :
Dept. Signal et Image, Inst. Nat. des Telecommun., Evry, France
Abstract :
Least-squares equation-error models are widely used as a simple means of estimating an input-output transfer function in a system identification context.. Although the models furnished by the least-squares method are not always stable, some recent works have shown that an autoregressive constraint on the input is sufficient to ensure stability of the furnished model. Here we provide a simple proof of this property for multivariable system estimation.<>
Keywords :
autoregressive processes; error analysis; estimation theory; identification; least mean squares methods; multivariable systems; numerical stability; transfer functions; autoregressive constraint; input-output transfer function; least-squares equation-error model; least-squares method; multivariable least-squares models; multivariable system estimation; stability; system identification; Autoregressive processes; Context modeling; Covariance matrix; Equations; MIMO; Polynomials; Stability; System identification; Transfer functions; White noise;
Journal_Title :
Signal Processing Letters, IEEE
