Genetic　regulatory　networks　is　a　kind　of　complex　nonlinear　dynamics　system.　The　stability　analysis　of　which　plays　an　important　role　in　the　study　of　life　science.　One　novel　genetic　regulatory　networks　was　defined　with　the　help　of　strong　modeling　ability　of　recurrent　neural　networks.　By　constructing　an　appropriate　Lyapunov-Krasovskii　function　according　to　the　characteristics　of　this　developed　model,　the　global　asymptotic　and　exponential　stability　were　established　through　linear　matrix　inequality　techniques　and　S-approach.　Finally,　the　performance　and　effectiveness　of　the　proposed　method　were　illustrated　with　numerical　examples.