查询词典 neural

In this paper,adaptive control approach of cupola based on neural network is brought forward and neural network as identification and controller is used to implement the self-adaption control of temperature of cupola molten iron.

提出了一种基于神经网络的冲天炉自适应控制方法，利用神经网络作为辨识器和控制器，实现对冲天炉熔炼过程中铁液温度的自适应控制。

This paper used Elman neural network to establish the model of irrigation water use prediction, having four importing units and exporting units. The determination of concealed level neural single number used the cut-and-try method, ten units were used.

运用神经网络中Elman反馈型神经网络建立了灌溉用水量预测模型，模型输入层神经元数目为4，输出层神经元数目为1，隐含层神经元数目确定采用试验法，最终确定为10。

According to compare the results with decision tree, support vector machine, and RBF neural network, the neural network classifier with dynamic threshold has better forecasting accuracy, stability and generalization ability.

通过与决策树、支持向量机、RBF网络等方法的比较结果表明，基于动态闽值的神经网络分类器具有更好的预测精度、稳定性以及泛化能力。

This paper has given a thorough investigation into the application of BP neural network to gravitational density interface inversion as well as the implementation of wavelet theory in potential field decomposition and, on such a basis, analysed and evaluated the prospect of applying wavelet neural network to the inversion of gravitational and magnetic data.

重磁数据处理是地球探测与信息技术学科中重磁方法、理论在生产实践工作中的重要环节，其中反演问题和位场分离除了具备自身的作用外，两者并不是截然分开的。位场分离可以为反演问题提供更加可靠的先验信息，对提高反演精度具有一定的作用。反演问题是地球物理的核心问题。增

This paper has given a thorough investigation into theapplication of BP neural network to gravitational density interface inversion as well as the implementation of wavelet theory in potential field decomposition and, on such a basis, analysed and evaluated the prospect of applying wavelet neural network to the inversion of gravitational and magnetic data.

文摘：对BP神经网络在重力密度界面反演以及小波分析在位场分离上的应用进行了深入的研究，进而对小波神经网络在重磁资料反演中的应用前景进行了分析、评价。

The results showed that neural network structure of tobacco aroma components was global optimized, and the neural network trained by genetic algorithm was more efficient and correct than by gradient descent method .

结果表明，使用该方法能全局优化基于烟草致香成分的神经网络结构，较之梯度下降法的神经网络的训练效率更高，得到的识别结果也更加准确。

By transforming the delayed neural model to the describer model and then employing the Lyapunov-Krasovskii stability theorem, linear matrix inequality LMI technique, S procedure, and some algebraic inequality method, a new sufficient condition is derived, which is determined by the coefficients of the model and includes more tuning parameters for determining the globally asymptotical stability of recurrent neural networks with time-varying delay.

首先将要研究的模型转化为描述系统模型，然后利用Lyapunov-Krasovskii稳定性定理、线性矩阵不等式技术、S过程和代数不等式方法，得到了确保时变时滞递归神经网络渐近稳定性的新的充分条件，并将它应用于常时滞神经网络和时滞细胞神经网络模型，分别得到了相应的全局渐近稳定性条件。

Thirdly, in order to improve the learning efficiency and stability of feedforward neural network, a fast learning algorithm for neural networks based on CGM-OC approach is presented. Compared with other learning methods such as BP method, Broyden Flecher Goldfarl Shanno method and Powell method in which the derivative is replaced by the difference quotient etc, simulation results show that the proposed method is an efficient and fast one.

第三，为了提高前馈神经网络权值的学习效率及稳定性，提出一种基于正交校正共轭梯度优化方法的神经网络学习算法，通过与其它学习算法（如：BP算法、变尺度法、用差商近似代替导数的Powell法等）的比较，经仿真试验表明，本算法是一种高效、快速的学习算法。

BACKGROUND: Neural stem cells have the potential of self-proliferation and multiple directional differentiation, and can differentiate into various cells in the neural system under a certain condition.

摘要背景：神经干细胞具有自我增殖能力和多向分化潜能，一定条件下可以分化成神经系统的各种细胞，因此在神经损伤修复方面有着良好的应用前景。

BACKGROUND: Effective proliferation in vitro of neural stem cells and directional induction and differentiation of dopaminergic neurons play a key role in neural stem cell transplantation for treatment of degeneration of the nervous system and repair of injured nervous system.

背景：在神经干细胞移植治疗神经系统退行性变及修复神经系统功能损伤过程中，有效的神经干细胞体外增殖与多巴胺能神经元的定向诱导分化尤为关键。

The dissecting of samples in group2 were difficult. The root of pulmonary artery and ascending aorta failed to be unfolded because fibrous tissue was tough, right and left fibrous trigone were too firm to be solved by hand. Cardiac muscle fibers couldn't be stripped along myofibrillar trajectory since they were prone to break because of their friability.

组2的心脏解剖困难，表现为纤维组织坚韧，游离肺动脉非常困难；徒手无法松解左、右纤维三角，肺动脉和主动脉根部的游离非常困难；心肌纤维坚硬、质脆，解剖时容易断离成碎块，无法沿纤维走行方向剥离。

We have battled against the odds in a province that has become increasingly violent.

我们对在一个争夺日益激烈省的可能性。