TY - GEN
T1 - Studies of optimal memory for discrete-time fir filters in state-space
AU - Ramirez-Echeverria, Felipe
AU - Sarr, Amadou
AU - Ibarra-Manzano, Oscar G.
AU - Shmaliy, Yuriy S.
PY - 2012
Y1 - 2012
N2 - We address two efficient estimators of optimal memory for FIR filters in discrete-time state-space via the conditional mean square error and real measurement. In the latter case, the algorithm does not involve neither a reference nor the noise covariances, but requires a learning circle. Although a justification has been provided for the Kalman-like unbiased FIR filter, the estimators can be used universally. Testing by the two-state polynomial model has shown a very good correspondence with the predicted values.
AB - We address two efficient estimators of optimal memory for FIR filters in discrete-time state-space via the conditional mean square error and real measurement. In the latter case, the algorithm does not involve neither a reference nor the noise covariances, but requires a learning circle. Although a justification has been provided for the Kalman-like unbiased FIR filter, the estimators can be used universally. Testing by the two-state polynomial model has shown a very good correspondence with the predicted values.
KW - FIR filtering
KW - optimal memory
KW - unbiased Kalman-like filter
UR - http://www.scopus.com/inward/record.url?scp=84868236642&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84868236642&partnerID=8YFLogxK
U2 - 10.1109/SSP.2012.6319701
DO - 10.1109/SSP.2012.6319701
M3 - Conference contribution
AN - SCOPUS:84868236642
SN - 9781467301831
T3 - 2012 IEEE Statistical Signal Processing Workshop, SSP 2012
SP - 349
EP - 352
BT - 2012 IEEE Statistical Signal Processing Workshop, SSP 2012
T2 - 2012 IEEE Statistical Signal Processing Workshop, SSP 2012
Y2 - 5 August 2012 through 8 August 2012
ER -