函数的逼近 meaning in English
approximation of function
Examples
- This paper puts forward bp improvable algorithm and exponent prediction pattern depending on neural network " s approach ability to non - linear function . comparing with traditional prediction algorithm , bp algorithm is verified to be feasible and accurate on exponent prediction
本文借助神经网络对非线性函数的逼近能力，提出了bp算法的改进型算法及基于bp算法的指数预测模型，通过对比传统预测算法，证实改进后bp算法用于证券预测的可行性及准确性。 - First , it applies fuzzy logical in the abstract and non - linear dealing ability ; second , it applies neural net in the self - study and any functions approaching ability ? through combining above two ability , it can find a best p i d non - linear controlling regularity and achieve controlling on line of the unknown subject etco therefore , it not only can strengthen robust and intelligence of the system , but also make design simple and easily be requiredo in addition , the thesis also does many works on procedure of upper - computer and basic - controller and the whole system designed can be put into work immediately
根据啤酒发酵过程具有大惯性、时滞和非线性等特点，本论文还提出一种基于神经网络的模糊自适应pid控制方案，它一方面利用模糊逻辑的“概念”抽象能力和非线性处理能力，另一方面利用神经网络的自学习能力和任意函数的逼近能力，通过两者的有机结合寻找一个最佳的p 、 i 、 d非线性组合控制规律，以实现对未知对象进行在线控制，并具备适应控制环境变化的能力和自学习能力等。 - In rsdm , binary patterns are replaced by real - valued patterns , accordingly avoiding the coding process ; the outer learning rule is replaced by regression rule , therefore the model has not only the ability of pattern recognition but the ability of function approximation . the prearrangement of the address array bases on the distribution of patterns . if the distribution of patterns is uniform . then the address array is prearranged randomly , otherwise predisposed with the theory of genetic algorithm and the pruneing measure so as to indicate the distribution of patterns and improve the network performance . non - linear function approximation , time - series prediction and handwritten numeral recognition show that the modified model is effective and feasible
在rsdm中，以实值模式代替二值模式，避免了实值到二值的编码过程：以回归学习规则代替外积法，使该模型在具有识别能力的同时具有了对函数的逼近能力；地址矩阵的预置根据样本的分布采取不同方法，若样本均匀分布，则随机预置，否则利用遗传算法的原理和消减措施来预置地址矩阵，使之反映样本的分布，改善网络的性能。 - The approximation property of projection pursuit wavelet neural network ( ppwnn ) which is applied to non - linear function is studied , the convergence rate is given in this paper also . 3 . we demonstrate projection pursuit wavelet neural network ( wppnn ) has a good applicability by the approximation of five non - linear functions and the prediction of sunport and chaos time series and the use of edge detection
主要工作如下： ( 1 )建立了投影寻踪小波神经网络的数学模型、拓扑结构及非线性学习机理； ( 2 )证明了投影寻踪小波神经网络可以逼近非线性函数，并给出了其收敛速度； ( 3 )通过投影寻踪小波神经络对五种非线性函数的逼近和对太阳黑子、混沌时间序列的模拟预报以及投影寻踪小波学习网络在图象边缘检测中的应用，说明该网络具有很强的实用性。 - Based on the analysis of the methods for optimizing the fuzzy neural networks before , this paper has finished following works : 1 ) we proposed a learning algorithm based on tabu search for fuzzy neural networks based on the model of anfis proposed by jyh - shing roger jang . then used the system for one variable function ' s approximation . 2 ) based on the first research , we improved the tabu search algorithm for the purpose of approximating complex functions . 3 ) analysis the capabilities of tabu search , and discuss the approximation ability and generalization ability of the fuzzy neural networks system according to the compute results
本文在对以前的模糊神经网络参数学习算法进行分析的基础上，做了以下几个方面的工作： 1 )根据禁忌搜索算法的特点，在jyh - shingrogerjang提出的anfis模型的基础上，将禁忌搜索算法应用于模糊神经网络线性和非线性参数的学习上，并将该模型用于单变量函数的逼近； 2 )在第一阶段的基础上，对算法进行了改进，使改进后的算法能够适用于复杂的ii函数逼近问题; 3 )根据计算机仿真的结果，对禁忌搜索算法的性能进行了分析，并对该模糊神经系统的函数逼近能力和泛化能力进行了讨论。