Signal Processing for Digital Communications: Theory, Algorithms And Applications
Signal Processing for Digital Communications: Theory, Algorithms And Applications
Brief A receding horizon unbiased FIR filter for discrete-time state space models
Automatica (Journal of IFAC)
IEEE Transactions on Information Theory
Finite-memory problems and algorithms
IEEE Transactions on Information Theory
Unbiased FIR filtering of discrete-time polynomial state-space models
IEEE Transactions on Signal Processing
An alternative FIR filter for state estimation in discrete-time systems
Digital Signal Processing
Linear optimal FIR estimation of discrete time-invariant state-space models
IEEE Transactions on Signal Processing
Optimal and unbiased FIR estimates of clock state
SIP'10 Proceedings of the 9th WSEAS international conference on Signal processing
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
Unbiased predictive steering of local clocks utilizing GPS 1PPS time signals
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
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In this paper, we find the optimal horizons and sampling intervals, both in the sense of the minimum mean square error (MSE), for a one-parameter family of the discrete-time unbiased finite impulse response (FIR) filters. On a horizon of N"l points in the nearest past, the FIR and the model k-state are represented with the l-degree and m-degree polynomials, respectively. The noise-free state space model is observed in the presence of zero-mean noise of an arbitrary distribution and covariance. The approach is based on the following. The FIR filter produces an unbiased estimate if l=m. In order to reduce the noise, N"l needs to be increased. The model fits the increased horizon with a higher degree polynomial, ml. Minimization of the mean square error for ml gives the optimal horizon and sampling interval. Justification is provided for the global positioning system (GPS)-based measurements of the first state of a local crystal clock provided in the presence of uniformly distributed sawtooth noise induced by the GPS timing receiver.