对于存在实际层神经元的CMAC模型，讨论了压缩映射对网络学习收敛性的影响。
Also, the influence on learning convergence from compression mapping in those CMAC models with actual neurons is discussed.
经图像边缘检测应用结果表明，该算法对于加快网络学习的收敛性有着显著成效。
The results of image edge detection show that the algorithm has better convergence properties than the conventional backpropagation learning technique.
在理论分析的基础上，提出了协同博弈的强化学习算法，并证明了算法的收敛性。
On the basis of theoretical analysis, the cooperative game reinforcement learning method is proposed and its convergence is proved.
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