Speedometer identification has been researched for many years.The common approaches to that problem are usually based on image subtraction,which does not adapt to image offsets caused by camera vibration.To cope with ...Speedometer identification has been researched for many years.The common approaches to that problem are usually based on image subtraction,which does not adapt to image offsets caused by camera vibration.To cope with the rapidity,robust and accurate requirements of this kind of work in dynamic scene,a fast speedometer identification algorithm is proposed,it utilizes phase correlation method based on regional entire template translation to estimate the offset between images.In order to effectively reduce unnecessary computation and false detection rate,an improved linear Hough transform method with two optimization strategies is presented for pointer line detection.Based on VC＋＋ 6.0 software platform with OpenCV library,the algorithm performance under experiments has shown that it celerity and precision.展开更多
A novel approach of sequence pattern correlation has been applied to predict an expected amino acid sequence from CID ESI MS spectra. The proposed approach deduces sequence patterns with no help from known protein da...A novel approach of sequence pattern correlation has been applied to predict an expected amino acid sequence from CID ESI MS spectra. The proposed approach deduces sequence patterns with no help from known protein database such that it is useful to identify an unknown peptide or new protein. The algorithm applies a cross correlation to match an experimental CID spectrum with predicted sequence pattern generated from fragmentation information. The fragmentation knowledge of both y series and other non y series are utilized to generate the predicted sequence patterns. In contrast to the normal de novo approach, the proposed approach is insensitive to mass tolerance and non susceptive to spectral integrality with no need for selection of a starting point.展开更多
in this paper,the statistical prOPerties of random combination sequences are discussed.Thevalue of E{R(r)}and the upper bound of E{A(r)}are derived.In the end,a new method to find a longsequence with low autocorrelati...in this paper,the statistical prOPerties of random combination sequences are discussed.Thevalue of E{R(r)}and the upper bound of E{A(r)}are derived.In the end,a new method to find a longsequence with low autocorrelation value is given.展开更多
基金Supported by the National Natural Science Foundation of China (61004139)Beijing Municipal Natural Science Foundation(4101001)2008 Yangtze Fund Scholar and Innovative Research Team Development Schemes of Ministry of Education
文摘Speedometer identification has been researched for many years.The common approaches to that problem are usually based on image subtraction,which does not adapt to image offsets caused by camera vibration.To cope with the rapidity,robust and accurate requirements of this kind of work in dynamic scene,a fast speedometer identification algorithm is proposed,it utilizes phase correlation method based on regional entire template translation to estimate the offset between images.In order to effectively reduce unnecessary computation and false detection rate,an improved linear Hough transform method with two optimization strategies is presented for pointer line detection.Based on VC＋＋ 6.0 software platform with OpenCV library,the algorithm performance under experiments has shown that it celerity and precision.
文摘A novel approach of sequence pattern correlation has been applied to predict an expected amino acid sequence from CID ESI MS spectra. The proposed approach deduces sequence patterns with no help from known protein database such that it is useful to identify an unknown peptide or new protein. The algorithm applies a cross correlation to match an experimental CID spectrum with predicted sequence pattern generated from fragmentation information. The fragmentation knowledge of both y series and other non y series are utilized to generate the predicted sequence patterns. In contrast to the normal de novo approach, the proposed approach is insensitive to mass tolerance and non susceptive to spectral integrality with no need for selection of a starting point.
文摘in this paper,the statistical prOPerties of random combination sequences are discussed.Thevalue of E{R(r)}and the upper bound of E{A(r)}are derived.In the end,a new method to find a longsequence with low autocorrelation value is given.
