Markov chainMonte Carlo (MCMC)methods are powerful computational tools for analysis of complex statistical problems. However, their computational efficiency is highly dependent on the chosen proposal distribution, which is generally difficult to find. One way to solve this problem is to use adaptiveMCMCalgorithmswhich automatically tune the statistics of a proposal distribution during the MCMC ...

A photoplethysmography (PPG) signal provides very useful information about a subject's hemodynamic status in a hospital or ubiquitous environment. However, PPG is very vulnerable to motion artifacts, which can significantly distort the information belonging to the PPG signal itself. Thus, the reduction of the effects of motion artifacts is an important issue when monitoring the cardiovascular s...

Control of a class of uncertain nonlinear systems, which estimates unavailable state variables, is considered. A new approach for robust tracking control problem of satellite for large rotational maneuvers is presented in this paper. The features of this approach include a strong algorithm to estimate attitude, based on discrete extended Kalman filter combined with a continuous extended Kalman ...

Speech enhancement aims to improve speech quality by using various algorithms. The objective of enhancement is improvement in intelligibility and/or overall perceptual quality of degraded speech signal using audio signal processing techniques. Enhancing of speech degraded by noise, or noise reduction, is the most important field of speech enhancement. In this paper a Robust speech enhancement m...

As electricity demand continues to grow and renewable energy increases its penetration in the power grid, realtime state tracking becomes essential for system monitoring and control. Recent developments in phasor technology make realtime dynamic state estimation possible with high-speed timesynchronized data provided by synchronized Phasor Measurement Units (PMU). In this paper we present a two...

In this paper, a homogenous multi-sensor fusion method is used to estimate the trueangular rate and acceleration with a combination of four low cost (< 10$) MEMS Inertial MeasurementUnits (IMU). An information form of steady state Kalman filter is designed to fuse the output of four lowaccuracy sensors to reduce the noise effect by the square root of the number of sensors. A hardware isimplemen...

The main control problem of visual servoing is to cope with the delay introduced by image acquisition and image processing. This delay is the main reason for limited tracking velocity and acceleration. Predictive algorithms are one solution to handle the delay. The drawback of prediction algorithms is the bad prediction behavior for the discontinuity in the target motion, for example, a velocit...

This paper addresses the application of observer-based control techniques for the adaptive optics system of the LBT telescope. In such a context, attention is focused on the use of Kalman and H∞ filters to estimate the temporal evolution of phase perturbations due to the atmospheric turbulence and the telescope vibrations acting on tip/tilt modes. We shall present preliminary laboratory experim...

While the main objective of adaptive Filter-and-Sum beamforming is to obtain an enhanced speech signal for subsequent processing like speech recognition, we show how speaker localization information can be derived from the filter coefficients. To increase localization accuracy, speaker tracking is performed by non-linear Bayesian state estimation, which is realized by sequential Monte Carlo met...