Abstract
The optimal filtering error for a class of nonlinear cone-bounded filtering problems is analyzed for the case of observation noise intensity tending to zero. A sufficient condition for the resulting optimal error covariance matrix to tend to zero is derived by relating the nonlinear filtering problems to linear ones. The results are specialized for the case of nonlinear autoregressive moving-average (ARMA) processes. >
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