Details

Autor(en) / Beteiligte

• Nakamori, S
• Caballero-Águila, R
• Hermoso-Carazo, A
• Linares-Pérez, J

Titel

Second-order polynomial estimators from uncertain observations using covariance information

Ist Teil von

• Applied mathematics and computation, 2003-11, Vol.143 (2), p.319-338

Ort / Verlag

New York, NY: Elsevier Inc

Erscheinungsjahr

2003

Quelle

Access via ScienceDirect (Elsevier)

Beschreibungen/Notizen

• This paper presents recursive least mean-squared error second-order polynomial filtering and fixed-point smoothing algorithms to estimate a signal, from uncertain observations, when only the information on the moments up to fourth-order of the signal and observation noise is available. The estimators require the autocovariance and crosscovariance functions of the signal and their second-order powers in a semidegenerate kernel form, and the probability that the signal exists in the observed values.