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.
基于模糊神经网络算法研究了非线性系统的噪声消除问题，设计了一类非线性自适应逆噪声消除控制器。
Based on Fuzzy Neural Network, the noise canceling problem of the nonlinear system was studied. A type of nonlinear adaptive noise controller was proposed.
本文采用模糊神经网络算法对AT M网络进行连接接纳控制，仿真结果表明它比传统的算法有更好的效果。
This paper brings the fuzzy neural network algorithms into the call admission control in ATM networks. The simulation result shows that it has better effect than usual algorithms.
该系统具有神经网络的结构和学习算法，称模糊神经网络FNN。
This system, possesses the structure of neural net and learning algorithm, addressed as fuzzy neural net FNN.
针对工业过程中普遍存在的时滞、非线性、对象参数时变等特性，提出了一种基于最优预测的神经元模糊自整定PID控制算法。
To the widely existed characteristics of time-delay, non-linear and timevarying of parameters in the industry process, an adaptive neuron-fuzzy PID controller based on optimal prediction is presented.
提出了一种基于混沌变量的多层模糊神经网络优化算法设计。
An optimization algorithm design based on chaotic variable is proposed for multilayer fuzzy neural network.
第三部分对基于混沌优化算法的模糊优选神经网络预测模型进行研究。
In the third part, the prediction model of fuzzy optimal selection neural network based on chaotic optimization algorithm is studied.
针对高噪音环境中的语音识别问题，提出一种利用模糊神经网络进行语音数据融合的新算法。
A new algorithm of employing the fuzzy neural network is proposed to realize speech data fusion for speech recognition under high noisy condition.
针对船舶航向控制中模型参数变化引起的不确定性问题，提出一种基于动态神经模糊模型(DNFM)的自适应控制算法。
A dynamic neural fuzzy model (DNFM) based adaptive control algorithm for ship course control was developed to overcome uncertainties arising from changes of model parameters.
采用自组织计数传播网络（CPN）作为框架，结合改进的模糊控制算法，实现对发酵过程的模糊神经元控制。
The count propagation network (CPN) was taken as framework, combining an improved fuzzy control algorithm, to realize the fuzzy-neural control of fermentation process.
介绍了基于模糊神经网络算法的塑料饮料瓶自动分类系统，包括算法设计和系统实现。
A design of plastic bottle automatic classification system based on NeuroFuzzy network is introduced, which includes arithmetic and system realization.
模拟结果表明利用该算法训练的模糊层次神经网络具有较好的非逻辑归纳能力和特征抽取能力，并且学习速度也大大加快。
The simulation result is that the Fuzzy forward neural networks which is trained by this algorithm have good non-logic generalization and feature extraction ability, as well as fast learning speed.
针对模糊综合评判法主观性强，随机性大的缺点，引入模糊神经网络算法对其加以改进。
Because of the fuzzy comprehensive evaluation has subjective and random, we introduce the neural network to improve risk assessment model.
通过补偿模糊推理和快速学习算法的引入，使得补偿模糊神经网络在性能上优于一般的模糊神经网络。
Through the introduction of compensatory fuzzy inference and quick arithmetic, the property of compensatory fuzzy neural networks is superior to that of common fuzzy neutral networks.
本文对神经元算法和模糊控制算法在实际中的应用作了探讨。
Have probed into the neuron algorithm and controls the application in reality of algorithm fuzzily in this thesis.
设计了解析模糊控制器，并在此基础上引入了单神经元；根据智能积分的思想，研究了模糊神经元非模型控制算法。
Based on designing analytical fuzzy controller, fuzzy-neuron model-free control algorithm is studied by using single neuron and the thought of intelligent integral.
经对性能指标性质的分析给出了一种模糊神经网络的学习算法——二阶段变半径随机搜索法。
Based on the analysis of the performance index a new algorithm, two stage random search algorithm with variable radius, is put forward.
文章在综合利用模糊模式识别剔除噪音信息和BP神经网络拟合优势的基础上，设计了模糊神经网络新算法。
The paper comprehensively USES the superiority of fuzzy pattern recognition over rejecting noise information and BP neural network on simulation to design a new algorithm named fuzzy neural network.
对每个控制模块设计了相应的模糊优化控制算法，并用改进的BP神经网络实现算法的模糊关系。
Fuzzy optimal control arithmetic was designed for each module, and an improved BP neural network was introduced to implement the fuzzy relation.
研究了将神经网络与模糊逻辑融合交叉而形成的神经网络-模糊智能控制算法的特点和优越性。
In this paper, the characteristics and advantages of neuro fuzzy intelligent control algorithm, which is an intersection of neural networks and fuzzy logic, are studied.
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.
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.
新控制器在控制过程中借助模糊神经网络的自学习算法实现控制参数的在线调整。
The parameters of new controller can be adjusted on line based on the ability of fuzzy ne ural network.
新控制器在控制过程中借助模糊神经网络的自学习算法实现控制参数的在线调整。
The parameters of new controller can be adjusted on line based on the ability of fuzzy ne ural network.
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