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径向基

网络RBF; Radial Basis Function, RBF; RBFN

径向基

网络释义

径向基

RBF

单一径向基(RBF)神经网络是一种性能良好的前向网络,其既有生物背景,又与函数逼近理论相配,适合于多变量函数逼近。用遗传 …

Radial Basis Function, RBF

径向基（Radial Basis Function, RBF）神经网络径向基（） 4. 竞争学习神经网络 5. Hopfield神经网络神经网络 6.

RBFN

...）多元（Multiple）修剪（Prune） 径向基（RBFN）穷尽算法（Exhaustive Prune）防止过分拟合（Prevent overtrianing） …

RBFs

Isight4.5在之前响应面(RSM)和径向基(RBFs)神经网络等近似模型方法的功能上增加Kriging方法大大强化了其在近似建模方面 …

Radial Basis Probabilistic

径向基,RBF,音标,读... ... ) Radial Basis Function 径向基 ) Radial Basis Probabilistic 径向基 ) radial time-base 径向时基 ...

例句：

This kernel is proposed in this paper and is proved to be able to improve training speed and precision of the wavelet SVM .

文中提出并证明了一种新的径向基小波支持向量核，可提高小波 SVM 的训练速度和逼近精度。

The system matrices of the local linear models are full parameterized and normalized radial basis functions are used for the weights.

局部状态空间模型用全参数化形式描述，同时选用正则化径向基函数作为分状态的加权因子。

Radial basic function is a recent meshless interpolation technique . It has a very simply form and no correlation with the space dimensions.

径向基函数插值是一种新型的无网格插值方法，具有形式简单、空间维数无关等优点。

RBF network with high generalization is a good classifier , especially for larger number of samples .

径向基网络作为分类器具有很高的推广性能，有利于大容量样本的分类。

In this work, MLP is substituted by a radial basis function (RBF) network , which solves these problems successfully .

通过引入径向基函数（RBF ）网络替代多层感知器网络，较好地克服了这些缺点。

the noise level slightly affects the ability of the two RBF networks to identify the damage location arid extent .

噪声水平对 2 个径向基函数网络的损伤位置和损伤程度的识别能力方面的影响较小。

The test indicated that tile radial primary kernel function is the best classification method.

试验表明选用径向基核函数所得的分类效果最好。

A new method to deform surfaces using radial basis function is proposed by replacing the Euclidean distance as geodesic distance .

并把测地线距离应用于径向基函数，实现了一种曲面变形算法。

In this paper, radial basis function neural network was employed to approximate the nonlinear complex relationship of all factors .

本文使用径向基神经网络确定各个因素之间的非线性复杂关系。

RBF neural network based tuning of PID control of radial basis function with the seclusion of the three single-feed-forward network .

基于 RBF 神经网络整定的 PID 控制径向基函数具有单隐居的三层前馈网络。

This paper investigated a new estimation method of soil properties under moving load by using radial basis function(RBF) neural network .

研究了移动荷载作用下径向基神经网络在地基土的参数识别中的应用。

The classification effect of Polynomial kernel function is also contracted with Gaussian RBF kernel function.

还比较了多项式核和高斯径向基核的分类效果。

The experimental results show that RBF neural network can successfully approximate the weights of all factors .

实验表明，径向基神经网络可以很好的逼近各个因素之间的权重关系。

Afterward, its output is estimated by radial basis function neural network (RBFNN) for extracting SEP features .

后级使用径向基神经网络作信号拟合，提取 SEP 信号的特征。

The RBF neural network parameters could be optimized .

实现了径向基神经网络参数优化。

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