Matrix computations (3rd ed.)
Optimal horizons for a one-parameter family of unbiased FIR filters
Digital Signal Processing
Explicit Formula for Predictive FIR Filters and Differentiators Using Hahn Orthogonal Polynomials
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Unbiased FIR filtering of discrete-time polynomial state-space models
IEEE Transactions on Signal Processing
Fir smoothing of discrete-time polynomial signals in state space
IEEE Transactions on Signal Processing
Linear optimal FIR estimation of discrete time-invariant state-space models
IEEE Transactions on Signal Processing
Analysis of an LMS algorithm for unbiased impulse response estimation
IEEE Transactions on Signal Processing
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We investigate the noise power gain (NPG) as a measure of error for transversal estimators. The error upper bound (EUB) and lower one (ELB) are specified via NPG for the most general p-shift linear time-variant transversal estimator intended for filtering (p = 0), prediction (p 0), and smoothing (p K-state space signal models with M states measured. A fast iterative algorithm for NPG of the unbiased FIR estimator is provided along. Examples of applications are considered employing the two-state polynomial space model.