利用人脸检测结果，结合混合高斯模型，以人脸肤色为样本在线建立了具有针对性的人体肤色模型。
Since a human face has the similar skin color distribution with the human body, we can use the skin pixels in a detected face to build the skin color model of human body dynamically by GMM.
该方法以有限个理论计算数据为样本，采用多项式函数离线进行回归，在保证高的逼近精度的前提下，以显著提高在线计算速度为目的。
The presented method is more accurate for using polynomial regression of theoretical calculated data as sample off-line and is quicker for the reason of its fixed polynomial pattern on-line.
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.
对五百万汉字样本的测试中，应用此引擎的在线词典对有意义短字符串(不包括单字)代码页的识别率可以达到99%以上。
In an online dictionary which used this engineer as a sample, the recognition rate of short string's code pages can reach 99% on the test documents which include about five million Chinese characters.
并介绍了在线误差补偿硬件系统的实现方法，以及通过样本的合理选择和系统的学习来提高补偿系统的补偿能力。
The realization method of lined error compensation hardware system and the methods of advance its compensation ability by the reasonable selection swatch and by the system study were introduced.
该方法利用模糊似然函数对样本数据进行聚类，并使模糊模型的结构辨识和参数辨识能同时完成，从而实现模糊模型的在线辨识。
The proposed method can accomplish the structure identification and the parameter identification of the fuzzy model in the same time, and implements the on-line identification of the fuzzy model.
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.
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.
针对训练样本贯序输入时的极端学习机（ELM）训练问题，提出一种可实现在线训练的局域极端学习机（LELM）。
To reduce the computational cost of extreme learning machine (ELM) online training, a new algorithm called local extreme learning machine (LELM) was proposed.
针对训练样本贯序输入时的极端学习机（ELM）训练问题，提出一种可实现在线训练的局域极端学习机（LELM）。
To reduce the computational cost of extreme learning machine (ELM) online training, a new algorithm called local extreme learning machine (LELM) was proposed.
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