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neural相关的网络例句

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与 neural 相关的网络例句 [注:此内容来源于网络,仅供参考]

And gives a more direct and reliable method to analyze the dynamic characteristics of neural networks.

它将为小型神经元网络的动态特性分析提供了更直观、更可靠的手段。

The initialized parameters of neural networks are selected, which is directed by rough set theory, and the networks are trained by using a probability-based BP algorithm, which minimizes system errors.

首先,利用粗糙集理论对神经网络初始化参数的选择和确定进行指导,赋予各参数相关的物理意义;然后,以系统输出误差最小化为目标对粗糙神经网络进行训练,使其满足性能要求。

Finally, the research direction and key problem to be solved are also discussed for Neural Network controller.

最后讨论了神经网络控制器发展方向与亟待解决的问题。

OBJECTIVE: To study the effect of Xiangdan injection and growth factors on directional differentiation of UCB-MSCs into neural cells, and to compare with the effect of simple growth factor induction.

目的:拟采用传统中药香丹注射液联合生长因子诱导脐血间充质干细胞向神经细胞方向分化,并且与单纯生长因子的诱导作用进行比较。

In this paper, a new dynamic accuracy theory is developed. It called the theory of the tracing of dynamic measuring error. The total output error is discomposed to the internal units as well as the external noises. And its modeling methods are discussed. Wavelet neural network is an important method in modern signal processes.

近年来 ,国内外不少学者致力于动态测试方法及数据处理方法的研究,取得了一定的成果,但是对动态测试误差分析方法的研究还不够成熟,不能满足现代高精度测试的要求,需要深入研究新的理论和分析方法。

The book is divided into 10 chapters, including discrete and continuous system of PID control system, commonly used digital PID control, Expert PID and fuzzy PID control, neural PID control, genetic algorithm PID control, Multivariable decoupling PID control, several advanced PID control, gray PID control, PID control servo system, PID control in real time, ea

全书共分十章,包括连续系统和离散系统的 PID 控制,常用数字 PID 控制,专家 PID和模糊 PID 控制,神经 PID 控制,遗传算法 PID 控制,多变量解耦 PID 控制,几种先进的PID 控制,灰色 PID 控制,伺服系统 PID 控制,PID 实时控制,每种方法都通过 MATLAB 仿真程序进行了说明。

A adaptive radial basis function neural network model based on discrete particle swarm optimization algorithms is proposed.

提出了一种基于离散粒子群的自适应RBF网络模型。

In this paper, we mainly discuss the dynamical behavior of a discrete neural model.

本文主要分析了一类离散神经元模型的动力学行为。

In the recent 50 years, many models such as Multivariate Discriminant Analysis and Neural Network come out.

近五十年来,从多元判别分析等线性预测模型,到以神经网络模型为代表的各种非参数预测模型,相关的研究成果层出不穷。

Compared with the traditional discriminant analysis method and neural networks method, this method has a distinct superiority.

近年嵘起的神经网络技术也为模式分类提供了新方法,但设计和训练较为

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