| 1. | The fusion rules and fusion operators are very important for image fusion
对于图像融合来说，融合规则和融合算子是十分重要的。 |
| 2. | A decision - making model and a numerical approach of partner selection were proposed based on multiple classifier fusion rules
应用多分类器融合规则，建立了供应链伙伴选择的决策模型和方法。 |
| 3. | Based on introducing wavelet analysis using in image fusion area , the existing fusion rules and fusion operators are presented
在引入小波分析用于图像融合的基础上，对现有的常用的融合规则和融合算子进行了介绍。 |
| 4. | The fusion rules of these models are analyzed and their effectiveness to improve the location performance is demonstrated by simulation
论文对两种模型的融合规则进行了分析，通过仿真验证了这两种模型对提高移动台定位性能的有效性。 |
| 5. | After analysed the performance of nonparametric detector particularly , three new fusion rules are proposed based on local statistics , their asymptotic relative efficiency is studied
在详细分析非参量检测器的理论基础上，提出了三种基于局部统计量的融合规则，分析了其渐进性能。 |
| 6. | Different fusion rules are studied in this paper . a novel region - based measure fusion rule is given , and the corresponding fusion operators used for different fusion schemes are presented
提出了一种新的基于区域特性量测的融合规则，并给出了与之相应的、用于不同融合方法的融合算子。 |
| 7. | Based on wavelet decomposition this paper presented a fusion algorithm , which extracted the local edge info in subband images as fusion rule and fused two leather images with complementarity
基于小波分解，提出了一种融合算法，该算法在小波分解的子带图像中提取局部边缘信息作为融合规则，较好的实现了两幅互补皮革图像的融合。 |
| 8. | Several evaluation criteria are presented in this dissertation . using these evaluation criteria , we study how the number of decomposition levels , different fusion rules or the size of region for measure influence the image fusion performance
文中建立了几种评价方法和准则，利用这些评价准则，研究了分解层数、不同融合规则以及特性区域大小对融合性能的影响。 |
| 9. | Based on unsupervised classification , improve the original kononen neural network ( knn ) by modifying learning rate and kernel function . and developed two fusion rules based on the magnitude of providing recognition information of each information sources
1 )改进基本的kohonen神经网络( knn )学习率和核函数，并针对每个信息源对最终识别贡献的大小，提出加权与不加权两种融合规则。 |
| 10. | Through a series of experiments , what can be done to fusion performance by wavelet radix , the number of decomposition levels , different fusion of rules , the size of region for measure or threshold is studied according to valuation methods proposed in the paper
通过一系列图像融合实验，利用文中所提出的评测方法研究了不同小波基、不同小波分解层数、不同融合规则、不同特性区域大小、不同阈值对融合性能的影响，从而得到相关结论。 |
