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- training samples information 训练样本信息
- In this method, rule intensity is defined according to the number of misclassified training samples. 该算法根据误分类训练样本的数量定义规则强度。
- SVM is used to classify, which weakly depends on the quantity and quanlity of training samples. 在分类器设计方面,选用了对样本数量和质量依赖性小的支持向量机。
- Besides that, we adopted a bootstrapping method during network's training, successfully solving the deficiency of non-face training samples. 而改进后的BP网络缩短了学习时间,提高了学习效率,并在一定程度上避免了学习中的局部极小问题。
- The discrimination model is established from the training samples using BP algorithm,and then the samples is distinguished from the well-trained. 利用BP算法对训练样本进行学习,确定判别模型,根据已训练好的神经网络对样本进行判别。
- In the training of the neural network model (NNM) of the plant and the neural network controller (NNC), training samples are got from the state function of the plant. 在训练实现对象模型的网络和实现控制器的网络时,由状态方程产生训练样本。
- In this paper the training samples, training method of neural network and the way combined with ADRC is analyzed, and the valuable conclusion is obtained. 文中对神经网络的训练样本、方法及其与自抗扰控制器结合的方式进行了分析和讨论,并得出了有益的结论;
- Experiment result shows that as reserving typical samples and reducing training samples, the generalization performance and training efficient of the classifier are guaranteed. 仿真结果证实,由于保留了典型样本,减少了训练样本数量,从而保证了分类器的性能且训练效率较高。
- To boost the recognition performance in this one training sample application scenario, we extract context information as another cue for recognizing people. 为了在这单一训练样本的情况下提高人脸分类的识别性能,我们亦由输入的照片集中,萃取出前后文讯息,来做为分类判断的另一种线索。
- The algorithm can obtain the better classifiers by using less training samples,so it leads to more generalization and less training samples than the other learning models. 该算法能用较少的训练样本获得更佳的分类器,因此它的推广能力较好,且对训练要求的样本数也大大下降。
- The size of an audience estimated to exist in the population, based on sample information. 根据样本的信息,推断在总体人口中所存在的某种受众总量。
- In order to prevent causing network incorrectly incline with one of fault type after training, the number of training samples for every fault should be allocated averagely. 为了防止人为的造成训练后的网络过多的倾向于某一故障类型,各故障类型的训练样本数量不应相差太多。
- We need to learn how to decide objectively, on the basis of sample information, whether to accept or reject a hunch. 我们应该学会如何在样本信息的基础上,客观地决定接受还是拒绝某种预感。
- Its weighted training error and scaling factor cm is computed (step 3b).The weights are increased for training samples, which have been misclassified (step 3c). 计算错误率和换算系数cm(step 3b).;被错分的样本的权重会增加。
- The training samples of RBF Neural Network are determined by Uniform Experiment Design to accelerate training process and enhance approximate capacity of the neural network. RBF神经网络训练样本的选取则由均匀试验设计确定,以提高样本的代表性并大幅减少样本数量,从而加快网络的训练过程,加强网络的逼近能力。
- It is shown that the ability of wavefront reconstruction of LSI is better than HWS, for the indirect sampling information of wavefront with LSI is more than HWS. 结果表明,在相同输入波前、相同探测面元、相同拟合函数及阶数的情况下,横向剪切干涉仪的波前复原能力比哈特曼波前传感器强。
- Typical fault characteristics are selected as training samples and GA is used to optimize the structure and original weight distribution of BP networks. 该法采用故障的典型特征作为样本训练网络,遗传算法来优化BP网络的结构与初始权值分布的策略。
- In the flood insurance, the sample information gotten doesn't accord with the theory requset for the statistical sample. 摘要在洪水保险中,获得的样本信息不符合对统计样本的理论要求。
- This paper generalizes a method for class discrimination with the purpose of formulating dynamic random models starting from sample information. 提出了一种从样本信息开始建立动态随机模型的分类判别方法。
- Under the nonhomogeneous environment, the performance of the conventional statistical STAP degrades greatly due to lack of sufficient homogeneous training samples. 在非均匀环境下,由于缺乏足够的与待检测样本中干扰独立同分布的训练样本,常规统计STAP方法性能急剧下降。