提出了关键技术，包括：挖掘主题的定义方法、海量训练样本的在线生成和高性能数据挖掘算法。
The key technologies is proposed, including methods of definition of mining topics, online acquirement of extra large amount of training samples, and algorithms of data mining with high performance.
当训练样本线性可分时，本文证明前馈神经网络的在线BP算法是有限次收敛的。
In this paper we prove a finite convergence of online BP algorithms for nonlinear feedforward neural networks when the training patterns are linearly separable.
应用神经网络的误差反向传播算法(BP)和大量的实测数据样本训练出了能在线诊断四种加工状态的BP模型并成功地诊断了实际加工状态。
The BP algorithm of Artificial Neural Networks and lots of experimental samples were used in training the BP model which succeeded in diagnosing four kinds of operational status.
增量型的支持向量机训练算法的一个重要特点是可以用于实时在线训练支持向量机的模型，这将大大扩展支持向量机的应用范围。
An advantage of the incremental algorithm is that it can be used to train SVM model online, which largely extends the application area of SVM.
在自适应LMS算法基础上，提出了在线BP训练算法、收敛速度快。
Based on adaptive LMS algorithms, the on line BP algorithm with fast convergence speed is presented.
将该方法应用于转子系统在线故障诊断中，结果表明，所设计的算法具有训练速度快、测试时间短、分类准确率高等特点。
Experimental results show that the designed classifier has many advantages of high training speed, short test time and high classification accuracy on fault diagnosis for rotor systems online.
在发动机启动阶段离线训练神经网络，在发动机稳态过程可以采用离线或在线学习算法。
Neural network can be trained for off-lime condition in all flight or for on-line condition in the stabilizing process of the rocket engine running.
该文针对统计分类语音算法对训练数据的依赖问题，提出自适应算法在线动态更新分类模型。
Adaptive algorithm of speech detection based on statistical classification is presented to reduce the dependence of the training data.
该文针对统计分类语音算法对训练数据的依赖问题，提出自适应算法在线动态更新分类模型。
Adaptive algorithm of speech detection based on statistical classification is presented to reduce the dependence of the training data.
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