Recently, a typical neural dynamics called Zhang dynamics (ZD) has been developed for online solution of dynamic linear matrix-vector inequality. This paper show a summary result by presenting the discrete-time forms of such a ZD for dynamic linear matrix-vector inequality solving. Specifically, by exploiting four different kinds of Taylor-type difference rules, the resultant discrete-time ZD (DTZD) algorithms, which are called respectively the DTZD-I, DTZD-II, DTZD-III, and DTZD-IV algorithms, are established. These algorithms can achieve excellent computational performance in solving dynamic linear matrix-vector inequality. The theoretical and numerical results are presented to further substantiate the efficacy of the presented four DTZD algorithms