This paper presents new developments of parameter identification for MIMO discrete stochastic systems with random parameters. These algorithms are based on the stochastic approximation method.
本文讨论MIMO离散系统的随机时变参数基于随机逼近法的辨识问题。
And then, we present an approximation method for solving this probabilistic constrained stochastic programming, and prove certain convergence of the method under some conditions.
随后我们提出了求解这类概率约束随机规划的一种近似算法，并在一定的条件下证明了算法的收敛性。
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。
We first formulate the problem as a stochastic nonlinear programming problem and then propose a new simple method for solving it via some approximation techniques.
本文先把问题转化为一个随机非线性规划问题，然后用逼近技术给出一个简单的求解方法。
Then it is demonstrated that the other methods are all the approximation of the stochastic method.
论证了其它方法都是随机过程方法的近似。
Then it is demonstrated that the other methods are all the approximation of the stochastic method.
论证了其它方法都是随机过程方法的近似。
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