Adaptive filtering of a random signal in Gaussian white noise

We consider the problem of estimating an infinite-dimensional vector θ observed in Gaussian white noise. Under the condition that components of the vector have a Gaussian prior distribution that depends on an unknown parameter β , we construct an adaptive estimator with respect to β . The proposed method of estimation is based on the empirical Bayes approach.