查询词典 neural network

Based on polynomial interpolation and approximation theory,a Chebyshev orthogonal basis neural network is constructed in this paper.

根据多项式插值和逼近理论构造一个切比雪夫正交基神经网络，其模型采用三层结构并以一组切比雪夫正交多项式函数作为隐层神经元的激励函数。

The experimental results, show that the RBF neural network is suitable for solving the problem of scattered data interpolation on a surface, and is more efficient than traditional methods. Furthermore, it can be easily generalized to solve the scattered data interpolation problem in higher dimensions.

从应用结果来看，RBF网络适合于解决曲面离散点集的光滑插值问题，比传统的样条方法更有效、更方便，具有较好的使用价值，并且可以很容易地推广到求解高维散乱数据插值问题之中。

Besides, it makes the neural network transparent and interpretable.

模糊神经网络是一种能处理抽象信息的网络结构，具有强大的自学习和自整定功能。

The LCD display character is acquisited by CCD,after analysis with image process and artificial neural network theory,through grid and intersecting lines to pick up the character′s characteristic,recognize LCD display character,provide with a kind of interface for the instruments and equipments which have no standard interface with the computer but have a LCD display.

摘 要：利用CCD对LCD数码显示字符进行采集，在分析图像处理和神经网络理论的基础上，采用网格法与交线特征提取法，对LCD数显字符进行识别，为具有LCD数显而与计算机无标准通信接口的仪器仪表设备提供一种实用的无线接口。

A new fast intra prediction mode decision algorithm based on BP neural network is proposed.

提出了一种基于BP神经网络的快速帧内模式选择算法。

A new algorithm : inverse main element method using Gaussian point spread function of the characteristics the RBF neural network model, the image blind rehabilitation.

详细说明：提出一种新的算法：逆主元法，利用高斯点扩展函数的特性，在径向基神经网络的模型下，对图像进行盲目复原。

In feedforward control, the hysteresis nonlinearity of the piezoceramic actuator is modeled using the Preisach model and a neural network architecture using input-output data mapping as the inverse function of Preisach model is utilized.

前向补偿控制器设计方面，先以布列谢希之数学模式来模式化压电陶瓷的磁滞特性，再由实测值求得模式内之参数值，并应用类神经网路结构取代Preisach数学模式的反涵数以作为前向控制器之用。

Which is based on the proposed RBF neural network inverse controller and a proportion differential controller.

并提出一种基于RBF神经网络逆控制与比例微分控制相结合的双模控制策略。

For nonlinear multivariable systems, two neural network inverse system decoupling methods are given.

对非线性多变量系统，提出了神经网络逆系统解耦的两种新方法。

Artificial neural network inverse method is helpful to system stability and robustness when it is applied to nonlinear TCP flow process.

神经网络逆系统方法应用于非线性的流量控制过程中有助于系统稳定性和鲁棒性。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。