文件名称:Multi-Sensor-Data-Fusion
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [PDF]
- 上传时间：
- 2012-11-26
- 文件大小：
- 4.74mb
- 下载次数：
- 0次
- 提 供 者：
- y*
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
《多传感器数据融合》英文参考书，比较有参考价值，适合雷达专业的研究者！-‘Multi-Sensor Data Fusion’ebook，useful
for the researcher majoring in radar!
for the researcher majoring in radar!
(系统自动生成,下载前可以参看下载内容)
下载文件列表
Multi-Sensor Data Fusion
........................\front-matter.pdf
........................\Part I
........................\Part II
........................\Part III
........................\........\Bayesian Decision Theory .pdf
........................\........\Bayesian Inference .pdf
........................\........\Ensemble Learning .pdf
........................\........\front-matter.pdf
........................\........\Parameter Estimation .pdf
........................\........\Robust Statistics.pdf
........................\........\Sequential Bayesian Inference .pdf
........................\.......\Common Representational Format .pdf
........................\.......\front-matter.pdf
........................\.......\Sensor Value Normalization .pdf
........................\.......\Spatial Alignment .pdf
........................\.......\Temporal Alignment .pdf
........................\Part IV
........................\.......\front-matter.pdf
........................\.......\Sensor Management .pdf
........................\......\architecture.pdf
........................\......\front-matter.pdf
........................\......\introduction.pdf
........................\......\sensors.pdf
........................\Part V
........................\......\back-matter.pdf
........................\......\front-matter.pdf
........................\......\Sensor Management .pdf
........................\......\Software Sources .pdf
........................\front-matter.pdf
........................\Part I
........................\Part II
........................\Part III
........................\........\Bayesian Decision Theory .pdf
........................\........\Bayesian Inference .pdf
........................\........\Ensemble Learning .pdf
........................\........\front-matter.pdf
........................\........\Parameter Estimation .pdf
........................\........\Robust Statistics.pdf
........................\........\Sequential Bayesian Inference .pdf
........................\.......\Common Representational Format .pdf
........................\.......\front-matter.pdf
........................\.......\Sensor Value Normalization .pdf
........................\.......\Spatial Alignment .pdf
........................\.......\Temporal Alignment .pdf
........................\Part IV
........................\.......\front-matter.pdf
........................\.......\Sensor Management .pdf
........................\......\architecture.pdf
........................\......\front-matter.pdf
........................\......\introduction.pdf
........................\......\sensors.pdf
........................\Part V
........................\......\back-matter.pdf
........................\......\front-matter.pdf
........................\......\Sensor Management .pdf
........................\......\Software Sources .pdf