Gives applied methods for studying stochastic differential systems--in particular, the methods for finding the finite-dimensional distributions of the state vector and of the output of such systems, and also the estimation methods of the state and of the parameters of differential systems based on observations (filtering and extrapolation theory). Also studied are stochastic differential equations of general type with arbitrary processes and independent increments. The equations with Wiener processes are considered as a special case. The construction of stochastic differential systems in the book is based on Pugachev's equations for finite-dimensional characteristic functions of the processes determined by stochastic differential equations. Includes end-of-chapter problems.