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In this paper, a new approach based on convex analysis is introduced to solve the $H_\infty$ problem for discrete-time nonlinear stochastic systems. A stochastic version of bounded real lemma is proved and the state feedback $H_\infty$ control is studied. Two examples are presented to show the effectiveness of our developed theory., Comment: 29 pages, 4 figures, 36 references

The objective of this paper is to study detectability, observability and related Lyapunov-type theorems of linear discrete-time time-varying stochastic systems with multiplicative noise. Some new concepts such as uniform detectability, ${\cal K}^{\infty}$-exact detectability (resp. ${\cal K}^{WFT}$-exact detectability, ${\cal K}^{FT}$-exact detectability, ${\cal K}^{N}$-exact detectability) and ${\cal K}^{\infty}$-exact observability (resp. ${\cal K}^{WFT}$-exact observability, ${\cal K}^{FT}$-exact observability, ${\cal K}^{N}$-exact observability) are introduced, respectively, and nice properties associated with uniform detectability, exact detectability and exact observability are also obtained. Moreover, some Lyapunov-type theorems associated with generalized Lyapunov equations and exponential stability in mean square sense are presented under uniform detectability, ${\cal K}^{N}$-exact observability and ${\cal K}^{N}$-exact detectability, respectively.

This paper aims to develop the stability theory for singular stochastic Markov jump systems with state-dependent noise, including both continuous- and discrete-time cases. The sufficient conditions for the existence and uniqueness of a solution to the system equation are provided. Some new and fundamental concepts such as non-impulsiveness and mean square admissibility are introduced, which are different from those of other existing works. By making use of the $\mathcal{H}$-representation technique and the pseudo inverse $E^+$ of a singular matrix $E$, sufficient conditions ensuring the system to be mean square admissible are established in terms of strict linear matrix inequalities, which can be regarded as extensions of the corresponding results of deterministic singular systems and normal stochastic systems. Practical examples are given to demonstrate the effectiveness of the proposed approaches.