RT Journal Article
ID 1df7b4ab3754a048
A1 Bao, Feng
A1 Cao, Yanzhao
A1 Chi, Hongmei
T1 ADJOINT FORWARD BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS DRIVEN BY JUMP DIFFUSION PROCESSES AND ITS APPLICATION TO NONLINEAR FILTERING PROBLEMS
JF International Journal for Uncertainty Quantification
JO IJUQ
YR 2019
FD 2019-04-23
VO 9
IS 2
SP 143
OP 159
K1 forward backward stochastic differential equation
K1 jump diffusion processes
K1 adjoint processes
K1 Fokker-Planck equation
AB Forward backward stochastic differential equations (FBSDEs) were first introduced as a probabilistic interpretation
for the Kolmogorov backward equation, and the solution of FBSDEs is equivalent to the solution of quasilinear partial
differential equations. In this work, we introduce the adjoint relation between a generalized FBSDE system driven
by jump diffusion processes and its time inverse adjoint FBSDE system under the probabilistic framework without
translating them into their corresponding PDEs. The "exact solution" of a nonlinear filtering problem is derived as an
application.
PB Begell House
LK http://dl.begellhouse.com/journals/52034eb04b657aea,3f762e845665d4bd,1df7b4ab3754a048.html