Multiple signal extraction by polynomial filtering

Comparative performance of polynomial si

Comparative performance of polynomial signal extraction

✍ W. A. Porter 📂 Article 📅 1982 🏛 Springer 🌐 English ⚖ 482 KB

Blind adaptive FRESH filtering for signa

Blind adaptive FRESH filtering for signal extraction

✍ Zhang, J.; Wong, K.M.; Luo, Z.Q.; Ching, P.C. 📂 Article 📅 1999 🏛 IEEE 🌐 English ⚖ 251 KB

Computing observation weights for signal

Computing observation weights for signal extraction and filtering

✍ Siem Jan Koopman; Andrew Harvey 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 180 KB

Call for Papers: Statistical Signal Extr

Call for Papers: Statistical Signal Extraction and Filtering

📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 84 KB

The need to extract signals and other components from time series is a requirement in many empirical sciences, including Medicine, Engineering, Economics and Climatology, to name but a few. Nowadays, a wide variety of methods are available, including Wiener--Kolmogorov Filtering, Kalman Filtering, P

Call for Papers: Statistical Signal Extr

Call for Papers: Statistical Signal Extraction and Filtering

📂 Article 📅 2004 🏛 Elsevier Science 🌐 English ⚖ 85 KB

The need to extract signals and other components from time series is a requirement in many empirical sciences, including Medicine, Engineering, Economics and Climatology, to name but a few. Nowadays, a wide variety of methods are available, including Wiener--Kolmogorov Filtering, Kalman Filtering, P

Optimal filtering for polynomial system

Optimal filtering for polynomial system states with polynomial multiplicative noise

✍ Michael Basin; Joel Perez; Mikhail Skliar 📂 Article 📅 2006 🏛 John Wiley and Sons 🌐 English ⚖ 157 KB

## Abstract In this paper, the optimal filtering problem for polynomial system states with polynomial multiplicative noise over linear observations is treated proceeding from the general expression for the stochastic Ito differential of the optimal estimate and the error variance. As a result, the