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stochastic相关的网络例句

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与 stochastic 相关的网络例句 [注:此内容来源于网络,仅供参考]

A class of affine nonlinear system of single input-single output is investigated. Firstly, the nonlinear system is transformed into an equivalent linear system through a diffeomorphism transformation. The networked control problems for the delays are constant, stochastic and shorter than a sampling period, and long and stochastic are investigated respectively.

针对一类单输入-单输出仿射非线性系统,首先通过微分同胚变换实现了仿射非线性系统的无反馈精确线性化;然后基于精确化线性模型,分别讨论网络延时为常时滞,随机时滞小于一个采样周期和随机长时滞情况的控制问题。

CBFEC emphasizes direct correspondence of concepts in EC with its software architecture for ease of understanding and using; minimal coupling with specific problem structure for easy adaptation it to solve a large number of wholly different problems; interface-centered design for extendibility. To achieve those objects, the problem-solving method of EC is analyzed and the problem-solving procedure of EC is divided into three interactive aspects: population-based stochastic searching mechanism, problem specific information to implicitly guide the stochastic searching, and the observation and control of the computation procedure of EC. Then the key concepts of EC are identified in those three aspects; the normal implementations of those concepts are summarized; the interfaces represents those concepts in software are abstracted; the collaborations of components through those interfaces are designed. CBFEC is implemented on mainstream component software platform COM/DCOM (Component Object Model/Distributed COM from Microsoft), which includes interfaces definitions, commonly using EC components implemented those interfaces, such as Simply EA component, Steady State EA component, EA component, EA component, Population component, Tournament Selection component, Linear Ranking Selection component, Nonlinear Ranking Selection component, Random Number Generator component, etc, and the collaborations of those components through those interfaces.

具体的做法是把演化计算看作是基于组件的软件工程的一个应用领域:首先分析了演化计算求解问题的一般思路和方法,把演化计算问题求解过程分为:"设计基于群体的随机搜索机制"、"研究问题的性质并以此隐含地定义算法的搜索方向"和"求解过程的观察与控制"三个部分;然后分别找出各个部分中的关键概念,总结这些概念现有的一般实现方法,抽取其本质,以此结合设计模式来定义组件软件的接口;通过分析演化计算各个概念之间的相互联系来设计组件软件间通过接口的进行交互的方式;最后还在目前一种主流组件软件开发平台COM/DCOM(微软提出的组件对象模型)的基础上实现了常用的演化计算组件,如简单演化算法组件、稳态演化算法组件、演化算法组件、演化算法组件、种群组件、锦标赛选择策略组件、线性排名选择策略组件、非线性排名选择策略组件、随机数发生器组件等等。

Stochastic variables included driven accelerations, driven time, torques, frictions and damps were considered basically. In the first, Monte Carlo method was applied to generate stochastic variables and dynamical responds of mechanism. Secondly, the application of Artificial Neural Network was motivated by the approximate concepts inherent in reliability analysis and time consuming repeated analyses required for MC.

将驱动加速度、驱动时间、摩擦和阻尼力等作为随机变量,应用蒙特卡罗方法,取得动态参数样本,再利用人工神经网络方法,根据抽取的样本对网络进行训练,统计网络输出得到动态应力分布,进而求出机构动态强度可靠度。

The earthquake ground motion model is simulated as nonstationary stochastic process model that is used as equivalent stationary stochastic process.

将地震地面运动模型模拟为非平稳随机过程模型,对其进行等效平稳化。

Stochastic control system ; limited control ; exact controllability ; backward stochastic differential equation

本文组织如下,第二节引入主要定义,介绍倒向随机微分方程及彭有关随机精确能控性

Studies on statistical properties of spontaneous spike trains of single auditory nerve have shown that the distributing patterns of interval in spike trains represent Poisson distribution. Since Poisson distribution is one of the simplest stochastic processes, previous studies on spontaneous spike trains of single auditory nerve were performed primarily by assuming them as stochastic processes. Recently, further studies on nonlinear dynamic system show that we have not enough evidence to demonstrate the process, whose distribution of probability density is exponential, is Poisson process.

中文题名豚鼠听神经单纤维放电序列的非线性特性分析副题名外文题名 Analysis on nonlinear properties in spike trains of single auditory nerve fiber in guinea pig 论文作者林龙年导师孙心德教授学科专业生理学研究领域\研究方向听觉神经生物学学位级别博士学位授予单位华东师范大学学位授予日期2001 论文页码总数91页关键词听神经听觉神经生理豚鼠馆藏号BSLW /2001 /Q42 /41 对听神经单纤维自发放电序列的统计特性研究表明,听神经单纤维放电间隔呈泊松分布,而泊松过程是最简单的随机过程之一,因此以往的研究主要将听神经单纤维自发放电序列作为随机过程来处理。

Thus far, little has been known for the extreme value distribution of general structural dynamic stochastic responses, except for some special results, say, the Rayleigh distribution in the case of narrow - banded Gaussian stochastic processes.

由于基于首次超越破坏准则的结构动力可靠度问题可以转化为相应动力反应极值分布的积分问题,获取结构动力随机反应的极值分布具有重要的意义川。

Basic concepts of stochastic processes: family of finite dimensional distribution functions, numerical characteristics of stochastic processes.

随机过程的基本概念:有限维分布函数族,随机过程的数字特征。

Advanced course covering topics selected from: semimartingale theory, stochastic integrals, homogeneous chaos expansions, stochastic differential equations, Malliavin calculus, infinite dimensional processes, functional central limit theorems, Feynman-Kac formula, Feynman integral.

随机分析:高级课程,包括:半鞅理论,随机积分,齐次混沌展开,随机差分方程, Malliavin 微积分,,有限维过程,泛函中心极限理论, Feynman-Kac公式, Feynman积分,过滤理论的应用,无限粒子系统,量子力学,神经学中的随机模型。

A convergence of the section sum in stochastic sequence under finite state is produced with the help of same distribute and comparative function of stochastic sequenct.

利用随机序列的同分布性及比较函数,导出了有限状态随机序列部分和的一个收敛性质。

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