Mirror filter is used for the compensation of nonlinear distortions for electro-dynamic loudspeaker systems and is based on the nonlinear differential equations. The design of Mirror filter requires the estimated parameters of a target loudspeaker system. If you obtain the corresponding parameters of a target loudspeaker system and arrange Mirror filter designed using those parameters in front ...

We derive a nonlinear filter and the corresponding filter-based estimates for a threshold autoregressive stochastic volatility, (TARSV), model. Using the technique of a reference probability measure, we derive a nonlinear filter for the hidden volatility and related quantities. The filter-based estimates for the unknown parameters are then obtained from the EM algorithm.

This paper considers the problem of designing nonlinear FIR filters from a bottom-up approach, in which simple components with known characteristics are combined into more complex filter structures. The specific approach considered here is based on the concept of a clone from universal algebra, generalizing the FIR-median hybrid (FMH) filter construction. Results presented here illustrate the f...

A discrete time filter is constructed where both the observation and signal process have non-linear dynamics with additive white Gaussian noise. Using the reference probably framework a convolution Zakai equation is obtained which updates the unnormalized conditional density. Our work obtains approximate solutions of this equation in terms of Gaussian sum when second order expansions are introd...

In INS/GPS integration, the data fusion algorithm involves properly handling of nonlinear models. Therefore the nonlinear filtering methods have been commonly applied in the INS/GPS integration to estimate the state vector. The most popular and commonly used method is the Extended Kalman Filter (EKF) which approximates the nonlinear state and measurement equations using the first order Taylor s...

Midpoint filter is quite effective in recovering the images confounded by the short-tailed (uniform) noise. It, however, performs poorly in the presence of additive long-tailed (impulse) noise and it does not preserve the edge structures of the image signals. Median smoother discards outliers (impulses) effectively, but it fails to provide adequate smoothing for images corrupted with nonimpulse...

The Extended Kalman Filter (EKF) has long been the de-facto standard for nonlinear state space estimation [11], primarily due to its simplicity, robustness and suitability for realtime implementations. However, an alternative approach has emerged over the last few years, namely the unscented Kalman filter (UKF). This filter claims both higher accuracy and robustness for nonlinear models. Severa...

In this paper, a nonlinear and/or nonnormal filter is proposed using rejection sampling. Generating random draws of the state-vector directly from the filtering density, the filtering estimate is simply obtained as the arithmetic average of the random draws. In the proposed filter, the random draws are recursively generated at each time. The Monte-Carlo experiments indicate that the proposed no...

In this paper, a generalised spline filter, that has a unified description for both the linear spline filter and the nonlinear robust spline filter, is proposed. Based on the M-estimation theory, the general spline filter model can be solved by using an Iterated Reweighted Least Squared method which is also general for both the linear and nonlinear spline filter. The algorithm has been verified...