搜索结果: 1-7 共查到“信息与通信工程 Spectral”相关记录7条 . 查询时间(0.14 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Geometry and recovery of spectral-sparse signals
频谱稀疏信号 几何 恢复
2023/4/26
A NEW EFFECTIVE WAY ON VEGETATION MORNITORING USING MULTI-SPECTRAL CANOPY LIDAR
Remote Sensing Vegetation Monitoring Global-Environmental LIDAR Spectral
2014/4/25
Airborne Laser Scanning (ALS) has been a well-established tool for the measurement of surface topography as well as for the estimation of biophysical canopy variables, such as tree height and vegetati...
Semi-Supervised Discriminant Analysis via Spectral Transduction
Semi-Supervised Discriminant Analysis Spectral Transduction
2010/12/20
Linear Discriminant Analysis (LDA) is a popular method for dimensionality reduction
and classification. In real-world applications when there is no sufficient labeled
data, LDA suffers from serious ...
电子科技大学通信原理理论课件CH6 Random Processes and Spectral Analysis
电子科技大学 通信原理理论 课件 CH6 Random Processes Spectral Analysis
2009/8/10
电子科技大学通信原理理论课件CH6 Random Processes and Spectral Analysis。
Efficient discovery of abundant post-translational modifications and spectral pairs using peptide mass and retention time differences
post-translational modifications spectral pairs peptide mass
2010/12/20
Peptide identification via tandem mass spectrometry is the basic task of current
proteomics research. Due to the complexity of mass spectra, the majority of mass spectra cannot be interpreted at pres...
Mining Tandem Mass Spectral Data to Develop a More Accurate Mass Error Model for Peptide Identification,
Spectral Data Mass Error Model Peptide Identification
2010/12/17
The assumption on the mass error distribution of fragment ions plays a crucial role in
peptide identification by tandem mass spectra. Previous mass error models are the
simplistic uniform or normal ...
A Two-Phase Spectral Bigraph Co-clustering Approach for the 'Who Rated What' Task
Two-Phase Spectral Bigraph Co-clustering Approach the 'Who Rated What' Task
2010/12/17
This paper describes our approach for the “Who Rated What” task in KDD Cup 2007 competition. Given the Netflix data set that consists of more than 100 million ratings between 1998 and 2005, this task ...