经对性能指标性质的分析给出了一种模糊神经网络的学习算法——二阶段变半径随机搜索法。
Based on the analysis of the performance index a new algorithm, two stage random search algorithm with variable radius, is put forward.
将学习理论与鲁棒控制相结合，采用随机化算法针对实参数不确定系统讨论了鲁棒控制器的设计问题。
This paper combines learning theory with robust control and discusses robust control design problems involving real parameter uncertainty in control systems based on randomized algorithms.
随机树分类算法是一种有监督学习的模式识别分类算法，可有效地应用于增强现实系统中的特征识别与匹配。
Randomized tree is a supervised classification algorithm for pattern recognition, which can be effectively used in augmented reality feature recognition and matching.
利用具有不同激励函数的分组方法提高网络性能，并利用随机梯度算法确保学习过程不会陷入局部极值。
The network performance is much enhanced by using the method with different stimulating functions. The algorithm of random grading can efficiently avoid falling into local minimums.
在分析了目前的拥塞控制算法的基础上，将随机估计学习算法(SELA)和模糊逻辑的知识引入拥塞控制，提出了新的拥塞控制模型。
Based on analysis of the current congesting algorithm, a new congesting control mechanism is proposed, which employs SELA (stochastic estimator learning algorithm) and fuzzy logic controller.
推导得到两种迭代学习辨识算法：迭代学习贝叶斯法和迭代学习随机牛顿法。
Two prototype algorithms of iterative learning identification, iterative learning Bayes and stochastic Newton algorithms, are proposed with detail.
换句话说，让我们学习算法告诉我们，到标签的实例，随机选择，而不是他们。
In other words, we let the learning algorithm tell us which instances to label, rather than selecting them randomly.
换句话说，让我们学习算法告诉我们，到标签的实例，随机选择，而不是他们。
In other words, we let the learning algorithm tell us which instances to label, rather than selecting them randomly.
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