Cite
Exponential Stability Analysis for Delayed Semi-Markovian Recurrent Neural Networks: A Homogeneous Polynomial Approach.
MLA
Li, Xin, et al. “Exponential Stability Analysis for Delayed Semi-Markovian Recurrent Neural Networks: A Homogeneous Polynomial Approach.” IEEE Transactions on Neural Networks & Learning Systems, vol. 29, no. 12, Dec. 2018, pp. 6374–84. EBSCOhost, https://doi.org/10.1109/TNNLS.2018.2830789.
APA
Li, X., Li, F., Zhang, X., Yang, C., & Gui, W. (2018). Exponential Stability Analysis for Delayed Semi-Markovian Recurrent Neural Networks: A Homogeneous Polynomial Approach. IEEE Transactions on Neural Networks & Learning Systems, 29(12), 6374–6384. https://doi.org/10.1109/TNNLS.2018.2830789
Chicago
Li, Xin, Fanbiao Li, Xian Zhang, Chunhua Yang, and Weihua Gui. 2018. “Exponential Stability Analysis for Delayed Semi-Markovian Recurrent Neural Networks: A Homogeneous Polynomial Approach.” IEEE Transactions on Neural Networks & Learning Systems 29 (12): 6374–84. doi:10.1109/TNNLS.2018.2830789.