Digital Signal Processing
New Quasi-Deadbeat FIR Smoother for Discrete-Time State-Space Signal Models: An LMI Approach
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Brief paper: Initial-value system for linear smoothing problems by covariance information
Automatica (Journal of IFAC)
Recursive limited memory filtering and scattering theory (Corresp.)
IEEE Transactions on Information Theory
A geometric approach to the linear modelling
CSS'11 Proceedings of the 5th WSEAS international conference on Circuits, systems and signals
A geometric approach to a non stationary process
MMES'11/DEEE'11/COMATIA'11 Proceedings of the 2nd international conference on Mathematical Models for Engineering Science, and proceedings of the 2nd international conference on Development, Energy, Environment, Economics, and proceedings of the 2nd international conference on Communication and Management in Technological Innovation and Academic Globalization
Hi-index | 0.00 |
This paper addresses a new design method of recursive least-squares (RLS) finite impulse response (FIR) filter, using the covariance information of the signal and observation noise, and RLS Wiener FIR filter in linear discrete-time stochastic systems. The signal is observed with additive white noise. The signal is assumed to be independent of the white observation noise. The RLS Wiener FIR filter uses the following information: (1) The observation matrix for the signal, (2) the system matrix for the state vector, (3) the variance of the state vector.