Xiao Lin, Zhang Yunong
School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510006, China.
IEEE Trans Neural Netw. 2011 Oct;22(10):1676-84. doi: 10.1109/TNN.2011.2163318. Epub 2011 Aug 15.
By following Zhang design method, a new type of recurrent neural network [i.e., Zhang neural network (ZNN)] is presented, investigated, and analyzed for online solution of time-varying linear inequalities. Theoretical analysis is given on convergence properties of the proposed ZNN model. For comparative purposes, the conventional gradient neural network is developed and exploited for solving online time-varying linear inequalities as well. Computer simulation results further verify and demonstrate the efficacy, novelty, and superiority of such a ZNN model and its method for solving time-varying linear inequalities.
通过遵循张的设计方法，提出、研究并分析了一种新型递归神经网络[即张神经网络（ZNN）]，用于在线求解时变线性不等式。对所提出的ZNN模型的收敛特性进行了理论分析。为了进行比较，还开发并利用传统梯度神经网络来在线求解时变线性不等式。计算机仿真结果进一步验证并证明了这种ZNN模型及其求解时变线性不等式方法的有效性、新颖性和优越性。
