private double PointToAngle(Point AOrigin, Point APoint) { if (APoint.X == AOrigin.X) if (APoint.Y > AOrigin.Y) return Math.PI * 0.5f else return Math.PI * 1.5f else if (APoint.Y == AOrigin.Y) if (APoint.X > AOrigin.X) return 0 else return Math.PI else {
標(biāo)簽： AOrigin APoint Point PointToAngle
上傳時(shí)間： 2016-10-31
上傳用戶：zhyiroy
private double PointToAngle(Point AOrigin, Point APoint) { if (APoint.X == AOrigin.X) if (APoint.Y > AOrigin.Y) return Math.PI * 0.5f else return Math.PI * 1.5f else if (APoint.Y == AOrigin.Y) if (APoint.X > AOrigin.X) return 0 else return Math.PI else {
標(biāo)簽： AOrigin APoint Point PointToAngle
上傳時(shí)間： 2016-10-31
上傳用戶：sunjet
private double PointToAngle(Point AOrigin, Point APoint) { if (APoint.X == AOrigin.X) if (APoint.Y > AOrigin.Y) return Math.PI * 0.5f else return Math.PI * 1.5f else if (APoint.Y == AOrigin.Y) if (APoint.X > AOrigin.X) return 0 else return Math.PI else {
標(biāo)簽： AOrigin APoint Point PointToAngle
上傳時(shí)間： 2013-12-18
上傳用戶：rocketrevenge
DEW POINT CALCULATION ROUTINE
標(biāo)簽： CALCULATION ROUTINE POINT DEW
上傳時(shí)間： 2016-11-04
上傳用戶：風(fēng)之驕子
RBFMIP is a package for training multi-instance RBF neural networks
標(biāo)簽： multi-instance networks training package
上傳時(shí)間： 2014-01-23
上傳用戶：refent
BPMLL is a package for training multi-label BP neural networks. The package includes the MATLAB code of the algorithm BP-MLL, which is designed to deal with multi-label learning. It is in particular useful when a real-world object is associated with multiple labels simultaneously
標(biāo)簽： package multi-label includes networks
上傳時(shí)間： 2013-12-05
上傳用戶：xsnjzljj
CCE is a multi-instance learning method solving multi-instance problems through adapting multi-instance representation to single-instance algorithms, which is quite different from existing multi-instance learning algorithms which attempt to adapt single-instance algorithms to multi-instance representation
標(biāo)簽： multi-instance multi-insta adapting learning
上傳時(shí)間： 2014-01-14
上傳用戶：manlian
This toolbox contains re-implementations of four different multi-instance learners, i.e. Diverse Density, Citation-kNN, Iterated-discrim APR, and EM-DD. Ensembles of these single multi-instance learners can be built with this toolbox
標(biāo)簽： i.e. re-implementations multi-instance different
上傳時(shí)間： 2013-12-19
上傳用戶：haohaoxuexi
The TMS320C54x, TMS320LC54x, and TMS320VC54x fixed-point, digital signal processor (DSP) families (hereafter referred to as the ’54x unless otherwise specified) are based on an advanced modified Harvard architecture that has one program memory bus and three data memory buses. These processors also provide an arithmetic logic unit (ALU) that has a high degree of parallelism, application-specific hardware logic, on-chip memory, and additional on-chip peripherals. These DSP families also provide a highly specialized instruction set, which is the basis of the operational flexibility and speed of these DSPs.
標(biāo)簽： TMS 320 fixed-point processor
上傳時(shí)間： 2013-12-27
上傳用戶：宋桃子
提出了利用精密單點(diǎn)定位(precise point positioning,PPP)技術(shù)進(jìn)行海嘯預(yù)警的方法,并利用TriP軟件對(duì)實(shí)測(cè)浮標(biāo)數(shù)據(jù)進(jìn)行了處理,將得出的海面高數(shù)據(jù)和海嘯波模型疊加進(jìn)行了模擬分析。仿真結(jié)果表明,利用精密單點(diǎn)定位技術(shù)進(jìn)行海嘯預(yù)警,能夠監(jiān)測(cè)判斷海嘯的發(fā)生,并獲得海嘯波到達(dá)海岸的波高和時(shí)間,提供一定的預(yù)警信息。
標(biāo)簽： positioning precise point TriP
上傳時(shí)間： 2016-11-18
上傳用戶：agent
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