
doi: 10.1007/bf01599977
We consider the problem of optimal filtering of a scalar diffusion process measured by a monotone nonlinear sensor in a low-noise channel. The specific sensors considered are of the form \(h_ n(x)=| x|^ nsgn(x)\). This case represents a wide class of sensors with a critical inflection point,since it is the leading term in Taylor's expansion of the measurement function in the critical region. We give for the first time a formal asymptotic approximation of the conditional and of the mean square estimation errors of the optimal filter as interpolation formulas. We also construct an asymptotic approximation to the optimal filter and compare its performance with that of a constant gain filter.
Estimation and detection in stochastic control theory, optimal filtering, scalar diffusion process, asymptotic approximation, Series expansions (e.g., Taylor, Lidstone series, but not Fourier series), Diffusion processes, Filtering in stochastic control theory, Inference from stochastic processes and prediction
Estimation and detection in stochastic control theory, optimal filtering, scalar diffusion process, asymptotic approximation, Series expansions (e.g., Taylor, Lidstone series, but not Fourier series), Diffusion processes, Filtering in stochastic control theory, Inference from stochastic processes and prediction
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