本文对多分类器融合模式识别的设计方法进行了研究。
This paper studies the design of pattern recognition system based multiple classifiers combination.
提出了一种基于子带处理多分类器融合的说话人识别方法。
A method of speaker recognition based on sub-band processing and multi-classifier combination is presented.
多分类器组合策略有两类：多分类器融合和多分类器选择。
There are two strategies for multiple classifiers combination: multiple classifiers fusion and multiple classifiers selection.
针对空战目标识别中机型识别这一问题，提出了基于多分类器融合的识别方法。
Aiming at aircraft type recognition in the field of automatic target recognition, a method based on combining classifiers is proposed.
实验结果表明，该方法能够用可理解性好的模糊系统实现低错误率的多分类器融合。
The experimental results show that the proposed method can fuse multiple classifiers with low classification error rate based on comprehensible fuzzy systems.
针对电力电子电路中器件的参数故障诊断问题，提出一种基于模糊推理的分类器融合诊断方法。
Aiming at the parametric faults diagnosis of the power electronic circuits, a method based on classifiers fusion was proposed to diagnose the circuit by using the fuzzy inference process.
再对上述两种识别模型进行决策层融合研究，提出了基于分类器融合的刀具状态识别模型和方法。
Then two above recognition model are fused at decisional level, the model and method of cutting tool state recognition based on classifier fusion is proposed.
分析了多分类器融合算法的理论框架，并采用决策模板算法对蛋白质结构类的预测问题进行了研究。
We investigate the theoretical framework of multiple classifiers fusion, and apply the decision template algorithms to classify the protein secondary structural classes.
对分类器融合采用极大值法、极小值法、乘积法、均值法、中值法、投票法和各种决策模板融合方法。
The classifier fusion approaches include Maximum, Minimum, Product, Mean, Median, Major Voting fusion methods and decision template fusion methods.
本文分析了影响分类器精度的因素，并提出了三种基于在测试例集上分类表现效果的多分类器融合方法。
This paper analyzes the factors affecting the accuracy of classifier, and designs three methods combining multi-classifier based on their performance on test corpus.
为了能够客观描述股指期货委托行为所具有的二重性与实体差异性，本文探索建立了多分类器融合分类模型。
In order to objectively describe duality and entity difference of commission behavior of stock index futures, this article explored and established the multi-classifiers fusion classification model.
为改进多分类器系统的性能，提出一个多分类器融合模型，该模型将和规则与多数投票作为特例纳入其体系中。
Aiming at improving the classification performance, a combination model of multiple classifier systems is presented, which takes the Sum rule and majority voting as its special cases.
而基于模糊规则的模式识别方法是一类可理解性好的非线性方法，但迄今为止还没有被应用于多分类器融合问题中。
As a nonlinear method, the fuzzy rule-based pattern recognition has good comprehensibility, but has not been applied to the multiple classifier fusion.
多分类器组合是对决策层的数据进行融合。
The multiple classifiers combination fuses the decision level data.
为了提高航空结构的损伤识别精度和速度，提出了一种基于互信息分类器选择的多主体决策融合方法。
In order to improve the aviation structure's damage identification accuracy and rate, a multi-agent decision fusion based on the mutual information classifier selection is proposed in this paper.
首先介绍了数据融合的分类和异类传感器数据融合的应用优点。
In this paper, the classification of data fusion and application merits of dissimilar-sensor data fusion are discussed at first.
分别利用普通话情感语音库和德语情感语音库进行实验，结果表明，与几种传统融合算法相比，改进的排序式选举法能够取得更好的融合效果，其识别性能明显优于单分类器。
According to the continuous space model for emotion, an improved queuing voting algorithm was proposed to implement the fusion of multiple emotion classifiers for a good emotion recognition result.
为了解决在没有已知标签样本的情况下数据流组合分类决策问题，提出一种基于约束学习的数据流组合分类器的融合策略。
To resolve combining classifiers decisions among ensemble classification over data streams without labeled examples, a transductive constraint-based learning strategy was proposed.
本文在对该方法进行研究的基础上，为了提高检测的性能，对分类器的选取、训练方法、遮挡处理、结果融合等方面进行了研究。
We dedicated to the research of it. In order to improve its performance, we worked on the selection and training process of classifier, occlusion handling, multiple detection results merging.
在分类器设计环节，比较五种核非线性分类器，并根据宽带极化雷达目标散射数据的特点，使用融合分类的方法对目标进行分类。
In classification stage, five kernel-based classifications are used and compared, and fusion methods are designed for wide-band polarimetric radar target classification.
在分类器设计环节，比较五种核非线性分类器，并根据宽带极化雷达目标散射数据的特点，使用融合分类的方法对目标进行分类。
In classification stage, five kernel-based classifications are used and compared, and fusion methods are designed for wide-band polarimetric radar target classification.
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