所以，我们可以把-1看成一个常量输入，它的权系数theta在学习（或者用技术术语，称为培训）的过程中进行调整。
So, it is possible to treat -1 as a constant input whose weight, theta, is adjusted in learning, or, to use the technical term, training.
TLU通过改变它的权系数和阈值来学习。
Wilson提供足够的SQL来帮助您学习如何在关系数据库中通知数据，并且他还涵盖了表格、连接、求反和嵌套查询。
Wilson provides enough SQL to help you learn how to massage data in a relational database, and he also covers tables, joins, negation, and nested queries.
本文是为那些具有关系数据库经验并且希望学习如何编写Perl程序来访问DB2数据库的Perl程序员编写的。
This article was developed for Perl programmers who have experience with a relational database and would like to learn how write Perl programs that access DB2 database.
09-1983.07在湖南师范大学数学系数学专业学习，获理学学士学位；
9——1983.7, majored in mathematics in Department of Mathematics, Hunan Normal University, received a bachelor degree of science;
利用成绩转移权系数法的评价步骤，通过划分学生学习成绩等级，对教师的教学效果进行了评价和分析。
Using the evaluating step of result transition weight number method, this paper analysed the teaching validity of teachers by dividing the grade of result.
此外，通过遗传算法对模糊神经网络的学习速率和惯性系数等进行了优化，为控制系统实现最优控制提供了有力保证。
In addition, the paper makes use of Genetic Algorithms to optimize learning rates and inertia coefficients of Fuzzy-neural network, which can ensure that the controller achieves optimization control.
提出了一种利用遗传算法优化前向神经网络的结构和正则项系数的混合学习算法。
A hybrid learning approach is presented in which genetic algorithms are used to optimize both the network architecture and the regularization coefficient.
通过分析外语课堂焦虑量表的得分和英语平均成绩之间的相关系数，来检验外语学习焦虑对学习成绩的影响。
The correlation coefficients between the FLCAS scores of all subjects and their average grades were computed to test the effect of language anxiety.
该方法用幂级数多项式拟合传感器的非线性模型，多项式的系数可由神经网络学习算法得到。
The response of the sensor is expressed in terms of its output by a power series. The coefficients of the power series can be learned and determined by a simple neural algorithm.
首先研究了初始权值的范围、学习率和正则项系数对泛化性能和学习速度的影响。
First, this paper investigates the effect of initial weight ranges, learning rate, and regularization co-efficient on generalization performance and learning speed.
本文提出了知识转化系数、学习能力系数和知识刚度等概念，并相应建立了竞争能力的评价模型。
This paper presents the concept of knowledge transformation coefficient, learning ability coefficient and knowledge rigidity etc.
该方法采用样本训练自学习，自适应调整变增益系数。
The method enables to adjust the alterable gain coefficients by the sample data sets training and self-learning.
给出了样本数据的预处理以及学习因子、动量系数、隐含层结点数等诚然定方法。
Provided with the Algorithm to determine the pre-possessing of sample data, learning rate, momentum factor, the Number of Hidden Layer Nodes, etc.
网络学习结束后，得到输入层、中间层和输出层各单元的连接系数矩阵。
After studying network, coefficient matrix of each unit which includes input layer, intermediate layer and output layer was gained.
本文主要研究非线性大滞后系统的建模问题，提出用串级网络模型进行滞后补偿，并给出了网络模型权系数的学习算法。
The method of how to do the lag compensation by means of linking up the network model is presented in this paper, and the weight coefficient algorithm of the model may be provided in this process.
对神经网络的结构和学习算法进行了探索性研究，引入一种基于自适应增益系数改进的学习算法。
After exploratory researches for the structure and learning algorithm of neural network, an algorithm based on adaptive gain coefficient is presented.
研究一种收缩系数和扩展系数适时适当变化的单纯形优化学习算法。
A kind of simplex algorithm that its constringency coefficient and expanding coefficient are been changing appropriately in the process of searching optimization values is developed.
本文提出一种基于自适应预测的无损压缩方法，该方法利用神经网络模型自学习的能力，自适应的调整预测器的预测系数。
In this paper, a lossless compression method, based on adaptive prediction, is presented. This method USES neural network model to modify the prediction weight.
水印的提取不直接取多个系数中水印的平均值，而是采用了一种自学习智能化方法。
Not averaging watermark values extracted from one block, We use an intelligent method to get the last watermark.
最后，引入了基于元学习理论的组合预测，确保权重系数在0到1之间。
Finally, the combination forecasting based on meta-learning is introduced which ensure that the weight coefficient between 0 and 1.
分析了遗传系数学习时所遇到的问题，提出了鲁棒学习的概念和方法；
Primary problems in learning inherited parameters are analyzed and concept and methods of robust learning are presented.
生产应用中，采用短时、长时自学习方法对换热系数进行在线修正，进一步提高模型的预测精度和稳定性。
The variational method is utilized for the discretization of the governing transient conduction-convection equation, with heat transfer coefficients adaptively determined by the actual mill data.
模型的基础上，泰勒级数的系数调整控制功能的迭代学习法律，学习增益矩阵，通过LMI优化设计。
Based on the model, the Taylor series coefficients of control function are adjusted by an iterative learning law and the learning gain matrix is designed via LMI optimization.
在此基础上，本文提出了一种混合的方法，同时考虑这三个因素，动态调整学习率和正则化系数。
Based on this, this paper proposes a hybrid method that simultaneously considers these three factors, and dynamically tunes the learning rate and regularization coefficient.
小波神经网络的训练采用自适应调整学习率及动量系数的方法，以避免陷入局部极小值。
The self-adaptive learning rate and momentum coefficient are used to avoid the local minimum point in the training process of wavelet neural network.
该模型利用梯度和倍增因子相结合的优化算法实现特征系数的学习；
This NNSC model utilizes the optimized method that combines the gradient and multiplicative algorithm to learn the feature coefficients, and only the gradient algorithm to learn feature vectors.
应用神经网络理论，本文提出了圆弧破坏和楔体破坏的边坡安全系数估计的新方法，为解决安全系数估计的知识的学习问题，提出了一种推广学习算法。
With application of neural network theory, a new method has been proposed for direct estimation of the safety factor for circular and wedge failure of slopes.
应用神经网络理论，本文提出了圆弧破坏和楔体破坏的边坡安全系数估计的新方法，为解决安全系数估计的知识的学习问题，提出了一种推广学习算法。
With application of neural network theory, a new method has been proposed for direct estimation of the safety factor for circular and wedge failure of slopes.
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