In this paper we present a neural network extended Kalman filter for modeling noisy financial time series. The neural network is employed to estimate the nonlinear dynamics of the extended Kalman filter. Conditions for the neural network weight matrix are provided to guarantee the stability of the filter. The extended Kalman filter presented is designed to filter three types of noise commonly o...

This paper introduces a technique for tracking the movement of vehicles in consecutive video frames. The technique is based on a Kalman filter and a reliability point system. The Kalman filter predicts the most probable location of a detected vehicle in the subsequent video frame. This information is used by the tracking function to narrow down the search area for re-detecting a vehicle. The Ka...

The time delay calibration between Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs) is an essential prerequisite for its applications. However, the correspondences between LiDAR and IMU measurements are usually unknown, and thus cannot be computed directly for the time delay calibration. In order to solve the problem of LiDAR-IMU time delay calibration, this paper prese...

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 ...

This paper presents a comparative analysis between two current control strategies, constant source power and generalized Fryze current, used in Active Power Filter (APF) applications having three different modulation methods. The Hysteresis Band (HB) and first-order Delta-Sigma Modulation (DSM) as well as the second-order DSM is applied. The power section of the active power filter is viewed as...

: The extended Kalman filter (EKF) has been applied to inferring gene regulatory networks. However, it is well known that the EKF becomes less accurate when the system exhibits high nonlinearity. In addition, certain prior information about the gene regulatory network exists in practice, and no systematic approach has been developed to incorporate such prior information into the Kalman-type fil...

The Kalman Filter (KF) is a powerful tool in the analysis of the evolution of a dynamical model in time. The filter provides with a flexible manner to obtain recursive estimation of the parameters, which are optimal in the mean square error sense. The properties of KF along with the simplicity of the derived equations make it valuable in the analysis of signals. In this chapter an overview of t...

in the present study, field oriented control of step motor implementation has been analyzed sothat it can make a sensorless control. efficiency and facilities of step motor is more than othertypes of electromotor. therefore, the numbers of mechanisms and different types of turning canbe made into them. also controlling these motors is easier than other available motors. steppingmotor has been d...

Visual object tracking is the active area of research in the computer vision. Various techniques have being developed for the object tracking .Particle filter deals with the tracking of the objects having non linear motion .Particle filter has been used in for various fields and application efficiently. Proposed Technique is based on combination of kalman filter, mean shift and particle filter....