HOS-based orthogonal subspace algorithm for causal ARMA system identification

نویسندگان

  • Girish Ganesan
  • K. V. S. Hari
چکیده

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 for impulse response recovery and hence estimation of the ARMA parameters. The proposed method is shown to do well at low SNR values and when impulse response recovery is the key issue, it is shown to o!er reduction in computational complexity. ( 2000 Elsevier Science B.V. All rights reserved.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Bearing Fault Detection Using Higher-Order Statistics Based ARMA Model

Impulse response provides important information about flaws in mechanical system. Deconvolution is one system identification technique for fault detection when signals captured from bearings with and without flaw are both available. However effects of measurement systems and noise are obstacles to the technique. In the present study, a model, namely autoregressive-moving average (ARMA), is used...

متن کامل

Identification of an Autonomous Underwater Vehicle Dynamic Using Extended Kalman Filter with ARMA Noise Model

In the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. Since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. In this study, hydrodynamic coefficients of an autonomous un...

متن کامل

Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms

Neural networks are applicable in identification systems from input-output data. In this report, we analyze theHammerstein-Wiener models and identify them. TheHammerstein-Wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...

متن کامل

Multichannel ARMA modeling by least squares circular lattice filtering

This paper makes an attempt to develop least squares lattice algorithms for the ARMA modeling of a linear, slowly time-varying, multichannel system employing scalar computations only. Using an equivalent scalar, periodic ARMA model and a circular delay operator, the signal set for each channel is defined in terms of circularly delayed input and output vectors corresponding to that channel. The ...

متن کامل

Semi-Blind Channel Estimation based on subspace modeling for Multi-user Massive MIMO system

‎Channel estimation is an essential task to fully exploit the advantages of the massive MIMO systems‎. ‎In this paper‎, ‎we propose a semi-blind downlink channel estimation method for massive MIMO system‎. ‎We suggest a new modeling for the channel matrix subspace. Based on the low-rankness property, we have prposed an algorithm to estimate the channel matrix subspace. In the next step, using o...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Signal Processing

دوره 80  شماره 

صفحات  -

تاریخ انتشار 2000