提出了一类新的模糊神经网络结构。
DSP技术以及本文所提出的模糊神经网络结构为模糊神经网络控制在工程中的应用开辟了一条新路。
DSP technology and fuzzy neural network structure presented in the paper pave the way for the engineering application of fuzzy neural network controller.
对于复杂的诊断对象，本文提出了一种复合模糊神经网络结构，该神经网络结构集成了一系列模糊神经子网络，来完成故障分类任务。
In this paper, a hybrid fuzzy neural network architecture is proposed for complex diagnosis objects. A series of fuzzy neural sub networks are integrated to perform the task of fault classification.
提出了一个基于模糊集理论的新的神经网络结构及其学习算法。
This paper presents a novel neural network architecture based on fuzzy set theory, FIBP.
本文研究了模糊神经网络，用神经网络结构进行模糊推理，用BP算法调节和优化具有局部性的参数。
In this paper, fuzzy neural network was studied and fuzzy reasoning was realized by use of neural networks structure. BP algorithm is used to optimize local parameter.
本研究将一类模糊神经网络引入染色体识别中，并采用两级网络结构。
A fuzzy neural networks consisting of two nets was applied to chromosome recognition in this paper.
实验证明，模糊数据曲线确定的网络结构是接近最佳的，在训练速度和精度方面，效果优于神经网络建模算法。
Under the same condition, the precision and speed of fuzzy neural network algorithm was better than that of neural network.
本文首先介绍了模糊逻辑和神经网络的基本知识，并由此给出了标准的T - S模糊神经网络的网络结构及算法。
This paper introduced firstly the basic knowledge of fuzzy logic and neural network, then the network structure and algorithm of the standard T-S fuzzy neural network were presented.
文中探讨了一种用于提取模糊规则的RBF神经网络结构，提出了基于此网路结构的模糊隶属度函数学习算法，最后给出了用于验证该算法有效性的仿真实例。
The learning algorithm of membership function based on the RBF Neural Network is discussed and an example is given to demonstrate the validity of this algorithm.
模糊神经网络的设计包括网络结构辨识和参数辨识。
The design of fuzzy neural networks consists of structure identification and parameter identification.
模糊神经网络的设计包括网络结构辨识和参数辨识。
The design of fuzzy neural networks consists of structure identification and parameter identification.
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