stochastic approximation

Measurement of bio-oil thermal properties by using thermal probe method based on stochastic approximation method

利用随机近似热探针方法的生物油热物性研究

The sequence of recursive estimators is adopted for function minimization , and Spall 's simultaneous perturbation stochastic approximation method is extended , and then an algorithm for stochastic perturbation gradient approximation is proposed .

采用递归估计器的序列求函数的最小值，并扩展了Spall的同步扰动随机近似方法，进而提出随机扰动梯度近似算法。

A new approach for design centering based on stochastic approximation

随机逼近用于中心设计的一种新方法

Simulation study of stochastic approximation LMS algorithm of Adaline neural network

Adaline神经网络随机逼近LMS算法的仿真研究

Detection and control of eccentricity in a cold mill based on stochastic approximation method

随机逼近法对轧辊偏心信号的检测与控制

It is a method between the ' stable ' and the stochastic approximation .

它是一种介于稳定和随机逼近之间的方法。

The convergence of algorithms is proved by the classical stochastic approximation theory .

并利用随机逼近理论证明了上述三种情形下提出的算法的收敛性。

A Proposal of CAC Scheme Based on Dynamic Bandwidth Allocation Using Stochastic Approximation

基于随机逼近动态带宽分配的CAC研究

A Modified Dynamic Stochastic Approximation Algorithms under Correlated Case with ARMA Measurement Noise

相关量测噪声下的修正动态随机逼近算法

A New Method of Identification of Multivariable Systems : Stochastic Approximation Algorithm with Forgetting Factor

一种多变量系统辨识的新方法：带遗忘因子随机逼近法

Model-free Adaptive Control Based on Stochastic Approximation Algorithm

基于随机逼近算法的无模型直接自适应控制

Numerical Realization of the Continuous-Time Stochastic Approximation Identification for Stochastic Continuous Dynamical Systems

随机连续动态系统的连续时间随机逼近辨识的数值实现

A stochastic approximation for parameters Markov decision processes

参数Markov决策过程的随机逼近算法

Stochastic approximation approach to the power control problem APPROXIMATION THEOREMS ON LINEAR OPERATORS DERIVED FROM POWER SERIES

幂级数导生的正线性算子的逼近定理关于算子的最佳逼近问题

A Modified Dynamic Stochastic Approximation Algorithms of the Extremum

关于极值的修正动态随机逼近算法

A truncated stochastic approximation procedure with dependent measurement errors

在相关量测误差下的一种截尾随机逼近算法

Therefore , this paper pay much attention to the study of model-free direct adaptive control based on stochastic approximation algorithm .

因此，本文在对随机逼近算法进行研究的基础之上，主要侧重于研究基于随机逼近算法的无模型直接自适应控制。

A simple Algorithm of Model-Free Control with a Reformative Method of Simultaneous Perturbation Stochastic Approximation

一种简易的无模型控制算法&改进的同时扰动随机逼近控制

By assuming normal distribution and identical variances , its convergence is discussed using stochastic approximation theory .

在正态分布、同一方差的假设下，借助随机逼近理论讨论了它的收敛性。

Continuous-time two-step stochastic approximation procedure with varying truncations and an example of application

连续时间变界截尾的两步算法及它的一个应用

A modified dynamic stochastic approximation algorithm is presented and which Convergence in Cesaro average sense is proved .

提出了修正动态随机逼近算法，并证明它在C？aro意义下的（a，？）

Convergence of Pad é Stochastic Approximation of Quasi-analytic Function

一类准解析函数的随机padé啨逼近的收敛性

Constrained stochastic approximation procedure with randomly varying truncations

带约束的变界截尾随机逼近算法

Then by utilizing the features of this model an online optimization algorithm that combines policy gradient estimation and stochastic approximation is derived .

利用此模型的动态结构特性，结合在线学习估计梯度与随机逼近改进策略，提出动态电源管理策略的在线优化算法。

The periodical variation signal produced by the eccentricity in a cold mill is detected by using the method of stochastic approximation .

论述了用随机逼近法分析、估算在冷轧过程中由轧辊偏心引起的周期性变化信号。

The simultaneous perturbation stochastic approximation ( SPSA ) algorithm based on the random fuzzy simulation is provided to obtain the optimal production run length .

将随机模糊模拟和随机扰动近似算法结合，设计了获得最优生产时间的算法。

To solve dynamic bandwidth allocation , this paper use adaptive stochastic approximation algorithm to compute true bandwidth requirement of the aggregated ON / OFF traffic .

本文运用自适应随机逼近算法研究了ON/OFF信源模型的带宽估计及接入问题。

Method for convergence analysis of stochastic approximation algorithms has been proposed in this paper . It is shown how convergence analysis of a random series can be associated with the algorithm .

本文提出了随机逼近算法的收敛性分析的一种方法，该方法是直接用级数和的收敛性分析代替算法的收敛性分析。

New on policy modeless average payoff reinforcement learning algorithms are derived as stochastic approximation methods for solving the system of equations in average payoff Markov decision processes .

本文以随机逼近的形式，提出了一些用于求解平均奖赏Markov决策过程系统方程的在策略无模型激励学习算法。

Then for the case that the jumping parameter is known , an opti-mal Markov jump filter is obtained by using the complete square method and the stochastic approximation method .

当跳参数可知时，采用完全配方法以及随机逼近的思想设计最优Markov跳跃滤波器，滤波器的表达式只与当前时刻跳参数有关，而与以前历史时刻无关。