我不希望式中有这么多变量。
因此，一个多变量的函数没有通常的导数。
So, a function of several variables doesn't have the usual derivative.
实际上我们并不需要这么多变量。
增强包括使用了很多变量。
本文提出了一种新的多变量自校正前馈控制器。
In this paper, a new multivariable self-tuning feedforward controller is presented.
研究设计：预后因素多变量分析的随机对照试验。
Study Design. A randomized controlled trial with multivariable analyses of prognostic factors.
事实上，如果你有一个多变量函数，那么它的准则依然如此。
In fact, if you had a function of many more variables the criterion would still look exactly like that.
给你一个有很多变量的函数，这样说不定你就崩溃了。
See, I am trying to just confuse you by giving you functions that depend on various Numbers of variables.
本文提出了一种简单的多变量极点配置自校正解耦控制器。
In this paper, a simple multivariable decoupling pole assignment self-tuning con-troller has been presented.
因此，温室环境是多变量耦合、时变、非线性的复杂系统。
So the greenhouse is a multi-variable coupled, time-varying and non-linear complicated system.
摘要：数据收集的66个国家和运行一个多变量线性回归分析。
Abstract: Data was gathered for 66 countries and a linear multi-variate regression was run.
经多变量拟合，得到了离心力作用下螺旋推进器的强度计算公式。
The strength calculation formula of the screw propeller under the action of centrifugal force was obtained through multivariate fitting.
使用多变量cox比例风险模型来确定与早期新生儿死亡相关的因素。
Multivariate Cox proportional hazards models were used to identify factors linked to early neonatal death.
很多变量都有一些特殊的意义，这是正在使用它们的规则的一种功能。
A number of variables have special meanings that are a function of the rule they're being used in. The most commonly used are
本文讨论了存在未知扰动情况下如何设计双线性多变量系统的观测器问题。
The problem of designing an observer for bilinear multivariable systems in the presence of unknown disturbances is considered.
中储式球磨机制粉系统是一个多变量、强耦合的对象，数学模型难以建立。
Tube mill pulverizer system is a multi variable and strong coupling process, which is difficult for mathematical model establishing.
单元机组负荷系统是具有耦合的两输入两输出多变量系统，具有较大的惯性。
The unit load system is a two-input and two-output multivariable plant with coupling and inertia.
提出了一种多变量统计质量控制方法来减小由于过程扰动引起的产品质量变化。
A multivariable statistical quality control method was presented to decrease the variance in product quality by the influence of process disturbance.
目的：采用多变量分析确定经前路颈椎间盘切除融合术后疗效欠佳的预测因子。
Objective. Perform a multivariate analysis to identify important predictors of poor outcome following anterior cervical discectomy and fusion.
论文首先建立了变风量系统的多变量控制模型，奠定比较完整的数学分析基础。
The multivariable model of the VAV system is established, which is the fundamental of the mathematical analysis of systems.
它不仅能消除可测干扰的影响，而且可以应用到多变量系统实现自适应解耦控制。
It not only can cancel the effect of measurable disturbances but also can be applied to MIMO systems to realize adaptive decoupling control.
在多变量逻辑回归模型中，开发基于回归系数预测程序的一个简单的临床评分体系。
A simple clinical scoring system was developed on the basis of regression coefficients of predictors in a multivariable logistic regression model.
强化干预组终止实验前共随访3.4年(中位数)，用多变量模型分析此期间数据。
Data obtained during 3.4 (median) years of follow-up before cessation of intensive treatment were analyzed using several multivariable models.
上次我们看了，怎样利用拉格朗日算子，去求解一个受约束的，多变量函数的最大最小值。
OK, so last time we saw how to use Lagrange multipliers to find the minimum or maximum of a function of several variables when the variables are not independent.
该控制器不仅能完全消除可测干扰的影响，而且能应用到多变量系统，实现自造应解耦控制。
It can be used to cancel the effect of measurable disturbances completely, and applied to multivariable systems to realize adaptive decoupling control.
所设计的多变量内模控制器能使系统稳定解耦，所得到的闭环系统根据开环系统时滞来描述。
All the stabilizing IMC controllers and the resulted closed-loop systems were characterized in terms of the open-loop system's time delays.
今天我们将要试着理解，更多变量之间的关系，和怎样处理，一个依赖于几个相关变量的函数。
And, today we're going to try to figure out more about relations between the variables, and how to handle functions that depend on several variables when they're related.
我们介绍且激发课程的主题将朝向于实例学习法的问题设定，例如稀疏值中多变量函数近似的问题。
We introduce and motivate the main theme of the course, the setting of the problem of learning from examples as the problem of approximating a multivariate function from sparse data - the examples.
我们介绍且激发课程的主题将朝向于实例学习法的问题设定，例如稀疏值中多变量函数近似的问题。
We introduce and motivate the main theme of the course, the setting of the problem of learning from examples as the problem of approximating a multivariate function from sparse data - the examples.
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