| 1. | Approximate limit sampling data using fuzzy - tree model
模糊树模型对有限样本集的逼近 |
| 2. | In this paper , an intelligent decision control algorithm with limited samples is proposed firstly
首先给出模糊预测控制的有限样本的预测学习方法。 |
| 3. | Is it possible for an estimator to be biased in finite sample but consistent in large sample
一个估计量是否有可能在有限样本中是有偏的但又具有一致性？ |
| 4. | The theories and methods for high dimensional multispectral data classification with limited training samples are studied , which are parts of important research contents of national 863 hi - tech , 973 project and ministry of education phd fund
结合国家863计划项目、国防973项目和教育部博士点基金项目，研究了有限样本下基于机器学习的高维多光谱数据分类问题。 |
| 5. | Response surface and support vector machines are adopted to approximate the actual models in view of the quality characteristics of a product and the related design parameters , which ensures the accuracy and efficiency of constructing the surrogate models in the case of limited samples
该方法采用响应面和支持向量机来逼近产品质量特性与其影响因素的关系模型，保证了在有限样本条件下的建模效率和精度。 |
| 6. | Support vector machine ( svm ) is a new and very promising classification technique . the approach is systematic and properly motivated by statistical learning theory . training invovles separating the classes with a surface that maximizes the margin between them
统计学习理论是一种专门研究有限样本情况下机器学习规律的理论，它不仅考虑了对推广能力的要求，而且追求在现有有限信息的条件下得到最优结果。 |
| 7. | The experiment shows that the model enables to detect transformer faults with a higher diagnosis rate , under condition of small samples , the diagnosis rate for discharge fault samples gets 90 . 5 % , and 85 . 9 % for thermal fault samples
实例验证表明，该模型在有限样本情况下，能达到较高的变压器故障判断率，放电性故障样本正确判断率为90 . 5 % ，过热性故障样本正确判断率为85 . 9 % ，说明该模型具有很好的分类效果和推广能力。 |
| 8. | An interesting property of this approach is that it is an approximate implementation of the structural risk minimizaiton ( srm ) induction principle . in this thesis , the theory and method of support vector machines were studied in the given application , text - independent speaker recognition
支持向量机是在统计学习理论的基础上发展而来的一种新的模式识别方法，在解决有限样本、非线性及高维模式识别问题中表现出许多特有的优势。 |
| 9. | A bp neural networks is designed to learn and classify the result coming fom the combination and standardization of every energy measure matrix . the experiment proves that the recognition rate of the system can reach to 95 % or more when the number of the experimental sample is limited
将分解得到的各能量测度矩阵的组合经规范化后由bp神经网络进行学习和分类，实践证明此笔迹鉴别系统对实验中提取的有限样本的鉴别正确率可达95以上。 |
| 10. | Through the theory of light radiation and intensity , we can use the fewest leds to satisfy the luminous intensity demand . through image segmentation theory , we can accurately pick module up from the test stripe when it is put in wrong directions . through image processing theory , we can acquire correct information and avoid the bad effects from the asymmetric chemistry reaction and instability of the devices
用光的辐射和强度理论,我们计算出了获得足够图像强度所需的最少光源;用图像分割理论,我们在试纸条倾斜放置或有垂直方向上的偏移时,准确地提取出了各模块的数据;用平滑滤波和均值滤波理论,我们滤除了由于反应不均匀及硬件设备不稳定带来的噪声;用交遇区设计线性分类器的方法,我们降低了有限样本设计线性分类器带来的误差,提高了检验准确度。 |
