FIR filters and recursive forms for discrete-time state-space models
Automatica (Journal of IFAC)
Matrix computations (3rd ed.)
One-Dimensional Digital Signal Processing
One-Dimensional Digital Signal Processing
Fuzzy Control
Optimal horizons for a one-parameter family of unbiased FIR filters
Digital Signal Processing
Unbiased FIR filtering of discrete-time polynomial state-space models
IEEE Transactions on Signal Processing
Detection and tracking of MIMO propagation path parameters using state-space approach
IEEE Transactions on Signal Processing
Fir smoothing of discrete-time polynomial signals in state space
IEEE Transactions on Signal Processing
Brief A receding horizon unbiased FIR filter for discrete-time state space models
Automatica (Journal of IFAC)
Studies of the noise power gain as a measure of errors for discrete-time transversal estimators
NEHIPISIC'11 Proceeding of 10th WSEAS international conference on electronics, hardware, wireless and optical communications, and 10th WSEAS international conference on signal processing, robotics and automation, and 3rd WSEAS international conference on nanotechnology, and 2nd WSEAS international conference on Plasma-fusion-nuclear physics
A Kalman-like algorithm with no requirements for noise and initial conditions
NEHIPISIC'11 Proceeding of 10th WSEAS international conference on electronics, hardware, wireless and optical communications, and 10th WSEAS international conference on signal processing, robotics and automation, and 3rd WSEAS international conference on nanotechnology, and 2nd WSEAS international conference on Plasma-fusion-nuclear physics
Discrete p-lag FIR smoothing of polynomial state-space models with applications to clock errors
NEHIPISIC'11 Proceeding of 10th WSEAS international conference on electronics, hardware, wireless and optical communications, and 10th WSEAS international conference on signal processing, robotics and automation, and 3rd WSEAS international conference on nanotechnology, and 2nd WSEAS international conference on Plasma-fusion-nuclear physics
Filtering of discrete-time state-space models with the p-shift Kalman-like unbiased FIR algorithm
TELE-INFO'11/MINO'11/SIP'11 Proceedings of the 10th WSEAS international conference on Telecommunications and informatics and microelectronics, nanoelectronics, optoelectronics, and WSEAS international conference on Signal processing
FIR filtering of state-space models in non-Gaussian environment with uncertainties
TELE-INFO'11/MINO'11/SIP'11 Proceedings of the 10th WSEAS international conference on Telecommunications and informatics and microelectronics, nanoelectronics, optoelectronics, and WSEAS international conference on Signal processing
Effect of first- and second-order extensions on UFIR filtering of nonlinear models
AMERICAN-MATH'12/CEA'12 Proceedings of the 6th WSEAS international conference on Computer Engineering and Applications, and Proceedings of the 2012 American conference on Applied Mathematics
Unified forms for Kalman and finite impulse response filtering and smoothing
Automatica (Journal of IFAC)
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This paper addresses a general p-shift linear optimal finite impulse response (FIR) estimator intended for solving universally the problems of filtering (p=0), smoothing (pp0) of discrete time-invariant models in state space. An optimal solution is found in the batch form with the initial mean square state function self-determined by solving the discrete algebraic Riccati equation. An unbiased solution represented both in the batch and recursive forms does not involve any knowledge about noise and initial state. The mean square errors in both the optimal and unbiased estimates are found via the noise power gain (NPG) and a recursive algorithm for fast computation of the NPG is supplied. Applications are given for FIR filtering with fixed, receding,and full averaging horizons.