Design of RLS Wiener estimators from randomly delayed observations in linear discrete-time stochastic systems

作者：Nakamori Seiichi^*; Hermoso Carazo Aurora; Linares Perez Josefa

来源：Applied Mathematics and Computation, 2010, 217(8): 3801-3815.

DOI：10.1016/j.amc.2010.09.039

• Discrete-time stochasticsystem
• RLS Wiener filter
• RLS Wiener fixed-point smoother
• Randomly delayed observations
• Covariance information

This paper presents the design of a new recursive least-squares (RLS) Wiener filter and fixed-point smoother based on randomly delayed observed values by one sampling time in linear discrete-time wide-sense stationary stochastic systems. The mixed observed value y(k) consists of the past observed value (y) over bar (k - 1) by one sampling time with the probability p(k) and of the current observed value (y) over bar (k) at time k with the probability 1 - p(k). It is assumed that the delayed measurements are characterized by Bernoulli random variables. The observation (y) over bar (k) is given as the sum of the signal z(k) and the white observation noise v(k). The RLS Wiener estimators explicitly require the following information: (a) the system matrix for the state v

• 出版日期2010-12-15