Fuzzy basis function network (FBFN) based on t s fuzzy model is given. A general approach for fault information detection in unknown systems using FBFN is present.
给出了基于TS模型的模糊基函数网络(FBFN)，并提出了一种基于FBFN的未知系统故障信息检测通用方法。
This fuzzy neural network USES wavelet basis function as membership function whose shape can be adjusted on line so that the networks have better learning and adaptive ability.
这种模糊神经网络利用了小波基函数作为隶属函数，可在线根据误差调整隶属函数的形状，使模糊神经网络具有更强的学习和适应能力。
A classification method based on fuzzy vector space model and radial basis function network is presented in this paper.
文本提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。
For reinforcement learning control in continuous Spaces, a Q-learning method based on a self-organizing fuzzy RBF (radial basis function) network is proposed.
针对连续空间下的强化学习控制问题，提出了一种基于自组织模糊rbf网络的Q学习方法。
Aiming at the design difficulty for fuzzy neural network controller, an immune evolutionary algorithm is proposed to design the parameters of a radial basis function fuzzy neural network controller.
针对模糊神经网络控制器难于设计的问题，提出了一种免疫进化算法用于径向基函数模糊神经网络控制器参数的优化设计。
Aiming at the design difficulty for fuzzy neural network controller, an immune evolutionary algorithm is proposed to design the parameters of a radial basis function fuzzy neural network controller.
针对模糊神经网络控制器难于设计的问题，提出了一种免疫进化算法用于径向基函数模糊神经网络控制器参数的优化设计。
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