Strong Consistency of Parameters' Bootstrap Estimators in Two-Dimensional Exponential Signal Model

In this paper, we investigate the Bootstrap approximation for two-dimensional exponential signal model with noise, which has a wide applications in statistical signal processing, and give the Bootstrap estimators of the parameters by virtue of the construction method of Bootstrap approximation in regressive model and prove the strong consistency. By Monte-carlo simulation, the results indicate that Bootstrap estimators are better than Least-squares estimators when the noise do not obey the normal distribution.