FNN

The linear combination of the error and its derivative are selected as switch surface, and then the tendency law method is used to design VSC control law. T-S FNN is imported, so that the actual output can trail the given value.

选择误差及其各阶导数的线性集结作为切换面，用趋近律方法设计变结构控制律，引入T-S模糊神经网络，使实际输出始终跟踪给定值。

For the CIR problem, the structure and training algorithm of FNN are decided, the input and output of FNN are fuzzed and the algorithm is modified.

针对煤岩界面识别的具体问题，确定了模糊神经网络的具体结构和训练算法；对于网络的输入、输出进行了模糊化处理并对算法进行了修正。

An optimization design method was proposed for a Fuzzy-Neural Network ( FNN ) structure based on chaotic variables.

基于混沌变量,提出一种关于模糊 神经 网络结构的优化设计方法.

The Forecasting Model of Sand-Dust Storm Based on FNN

基于模糊神经网的沙尘暴预报模型

The theory of fuzzy neural network ( FNN ) modeling for nonlinear systems is presented.

摘要论述了模糊系统和 神经 网络相结合的非线性系统辨识理论.

FNN simulation indicates that the predicted results are more accurate than estimated with traditional method.

通过对试验数据的仿真计算,其强度预测精度高于常规的综合方法.

Based on Fuzzy Neural Network ( FNN ), an intelligent adaptive sliding mode guidance law is presented.

在自适应滑模导引律的基础上,提出了一种基于模糊神经网络 ( FNN ) 的自适应滑模导引律.

Then this paper attempts to optimize travel route using FNN because it has some similar physical properties with traffic network.

利用流体神经网络与道路交通网络具有相似性的特点，将流体神经网络技术引入交通网络的路线优化。

Experimental results indicate that FNN filter has better effect on impulse noise, Gaussian noise and mixed noise than VMF, especially on preserving edges and fine image details.

结果表明：模糊神经网络彩色滤波器无论对单纯的脉冲噪声及高斯噪声，还是二者的混合噪声，其滤除能力都要优于矢量中值滤波器，并且有较好的边缘和细节保持能力。

The simulation experiment with this method on a robot manipulator is implemented and good system performance is achieved. Moreover, using the fuzzy neural network ( FNN), a new intelligent terminal sliding mode controller is designed.

该方案在机器人手臂系统中进行了应用，取得了良好的控制效果。此外，提出了一种基于模糊神经网络的终端滑模控制设计方案。

Such a four-layer FNN constitutes a universal approximator of fuzzy valued function. That is, each continuous fuzzy valued function defined on any compact set of Euclidean space can be approximated by the FNN to any degree of accuracy.

该类网络构成了模糊值函数的一类泛逼近器，即在欧氏空间的任何紧集上，任意连续模糊值函数能被这类FNN逼近到任意精度。

Fuzzy inference network ( FIN ) and fuzzy associative memory network ( FAM ) are two most important FNN models.

模糊推理网络 ( FIN ) 和模糊联想记忆网络 ( FAM ) 是两种最重要的FNN模型.

Then, a new adaptive control method for nonlinear systems is presented by integrating robust modeless learning adaptive control theory for nonlinear systems and FNN.

然后，本文将非线性系统鲁棒无模型自适应控制理论与前馈神经网络相结合，提出一种基于前馈神经网络的非线性系统自适应控制方法。

Drawing of compensation based on FNN and Genetic Algorithms ( GA ) heightens the system anti-jamming capability.

FNN与遗传算法 ( GA ) 相结合形成的调整机制的引入,增强了系统的抗干扰能力.

The new FNN filter was compared with vector median filter ( VMF) using image Flowers and Lena.

用Flowers图像和Lena图像对经过训练的滤波器和矢量中值滤波器进行了测试对比。

The FNN constituted by NGA, whose convergence rate, optimizing capability and distinguish effect are superior to those of GA and BP, is accorded with project need of discriminating.

以NGA训练的模糊网络模型，在收敛速度、寻优能力和辨别效果方面均优于BP、GA算法下的模型，符合缺陷识别的工程需要。

TSK FNN which composed of TSK fuzzy system and pi-sigma neural net has the advantages of both neural net and fuzzy system.

因此我们考虑将TSK模糊神经网络应用到经济预警上，它同时具有神经网络自适应能力强和模糊系统可以处理专家经验的优点。

This paper has researched motor power characteristic, adopted Fuzzy Neuro Network Controller ( FNN) to confirm target current and utilized PID controller to tail after target current.

对电机助力特性控制进行了研究，采用模糊神经网络控制方法确定电机的目标电流，并利用PID控制跟踪目标电流。

A diagnosis model of auto-production line based on FNN and data fusion technology was established.

在此基础上,建立了基于模糊神经网络与信息融合技术的自动生产线故障诊断模型.

Optimizing neuronal activation function types based on GP in constructive FNN design

前馈网络构造性设计中基于GP实现神经元激活函数类型优化