This paper aims to reveal the relationship between the minimum L2-sensitivity of state-space digital filters and the Gramian-preserving frequency transformation. To this end, we first give a prototype low-pass state-space filter in such a manner that its structure becomes the minimum L2-sensitivity structure. Then we apply the Gramian-preserving (LP-LP) frequency transformation with a tunable p...

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. Rece...

One of the most important problem in target tracking is Line Of Sight (LOS) rate estimation for using from PN (proportional navigation) guidance law. This paper deals on estimation of position and LOS rates of target with respect to the pursuer from available noisy RF seeker and tracker measurements. Due to many important for exact estimation on tracking problems must target position and Line O...

no on-site sanitation system treats both urine and faecal matter in one process. a laboratory scale biological filter was fed with high concentration of urea (4 g n/l) and 17.1 g cod/l to determine if it will be possible to treat liquid that leach from a ventilated improved pit latrine. the hlr in the proposed biological filter system was calculated to be ca 36 l/m2/d, significantly lower than ...

An enhanced and optimized adaptive filter with optimal filter coefficients selection is proposed and implemented to resolve motion artifact issue in wearable ECG Recording. A two-electrode small size chest belt ECG system mounted with 3-axis accelerometer is implemented for ECG and activity ubiquitous recording in daily life. In ubiquitous ECG recording, ECG signal is often distorted due to dif...

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state-variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This...

Recently, particle filters have attracted attentions for nonlinear state estimation. In this approaches, a posterior probability distribution of the state variable is evaluated based on observations in simulation using so-called importance sampling. We proposed a new filter, Evolution Strategies based particle (ESP) filter to circumvent degeneracy phenomena in the importance weights, which dete...

In this paper, Particle Filter algorithm has been employed for estimating the states namely concentration and temperature of a Continuous Stirred Tank Reactor (CSTR) and simulation results are presented. The propagation of particles through the nonlinear system model for the state estimation has been discussed. The states of the system are estimated by using the Particle Filter algorithm under ...

In this work, a novel nonlinear filter, called tri-state median (TSM) filter, is proposed for preserving image details while effectively suppressing impulse noise. We incorporate the standard median (SM) filter and the center weighted median (CWM) filter into a noise detection framework to determine whether a pixel is corrupted, before applying filtering unconditionally. Extensive simulation re...