Digital spectral analysis: with applications
Digital spectral analysis: with applications
Multichannel Time Series Analysis with Digital Computer Programs
Multichannel Time Series Analysis with Digital Computer Programs
Signal Processing - Fractional calculus applications in signals and systems
Fast communication: Fast filtering of noisy autoregressive signals
Signal Processing
Order selection criteria for vector autoregressive models
Signal Processing
The Journal of Supercomputing
Hi-index | 0.08 |
We present a new multichannel autoregressive parameter estimation method using a finite set of noisy observations without a priori knowledge of additive noise power. The proposed method is based on soving alternatively a set of nonlinear and a set of linear equations. The Newton-Raphson iteration algorithm is used to estimate the unknown noise variances solving the nonlinear equations while the unknown AR parameter matrices are estimated solving the noise-compensated Yule-Walker equations linearly. Computer simulation results are presented to evaluate the performance of the proposed method.