Estimation of change point via Kalman-Bucy filter for linear systems driven by fractional Brownian motions

Estimation of Change Point via Kalman-bucy Filter for Linear Systems Driven by Fractional Brownian Motions

We study the estimation of change point obtained through a Kalman-Bucy filter for linear systems driven by fractional Brownian motions.

Filtering for Linear Systems Driven by Fractional Brownian Motion

Stochastic differential equations driven by fractional Brownian motions

2 Young’s integrals and stochastic differential equations driven by fractional Brownian motions 4 2.1 Young’s integral and basic estimates . . . . . . . . . . . . . . . . . . 4 2.2 Stochastic differential equations driven by a Hölder path . . . . . . . 7 2.3 Multidimensional extension . . . . . . . . . . . . . . . . . . . . . . . 11 2.4 Fractional calculus . . . . . . . . . . . . . . . . . . . ...

Fixed-point FPGA Implementation of a Kalman Filter for Range and Velocity Estimation of Moving Targets

Tracking filters are extensively used within object tracking systems in order to provide consecutive smooth estimations of position and velocity of the object with minimum error. Namely, Kalman filter and its numerous variants are widely known as simple yet effective linear tracking filters in many diverse applications. In this paper, an effective method is proposed for designing and implementa...

Title Maximum Principle for General Controlled Systems Driven by Fractional Brownian Motions

We obtain a maximum principle for stochastic control problem of general controlled stochastic differential systems driven by fractional Brownian motions (of Hurst parameter H > 1/2). This maximum principle specifies a system of equations that the optimal control must satisfy (necessary condition for the optimal control). This system of equations consists of a backward stochastic differential eq...