例句與造句

1. Returns the matrix transpose of a given matrix
   返回一個(gè)給定矩陣的轉(zhuǎn)置矩陣。
2. Matrix object that is the matrix transpose of the matrix
   對(duì)象，該對(duì)象是此矩陣的轉(zhuǎn)置矩陣。
3. The results indicate that the serial and parallel optimization for fft , phase compensation and matrix transpose has the most significance for sar imaging performance
   分析結(jié)果認(rèn)為，對(duì)sar成像處理的優(yōu)化，主要是對(duì)fft 、相位補(bǔ)償運(yùn)算和矩陣轉(zhuǎn)角運(yùn)算等3類(lèi)典型運(yùn)算的串行優(yōu)化和并行優(yōu)化。
4. The fast dct algorithm not only can reduce the multiplication number , but also can combine the post - scaling and matrix transpose needed for fast dct with the quantization and scan processes , so as to speed up the whole mpeg encoder . in addition , the table - lookup fast quantization algorithm can further speed up the encoding process
   本章提出的快速dct算法不僅減少了所需乘法的次數(shù)，而且變換后的后置乘法和矩陣轉(zhuǎn)置過(guò)程可與量化和掃描相結(jié)合，進(jìn)一步加速浙江大學(xué)博士學(xué)位論文整個(gè)mpeg編碼過(guò)程。
5. Also , the relactions between the best block size for matrix transpose and the size and associativity of the processor ' s cache is formulized . for parallel optimization , several programming models available on a numa system , such as lightweight processes ( sproc ) , posix threads , openmp and mpi , are compared , and their speedup and coding complexity are analyzed
   對(duì)于sar成像處理的并行優(yōu)化，本文對(duì)比了在numa架構(gòu)上可用的幾種并行編程模型：輕量級(jí)進(jìn)程、 posix線程、 openmp和mpi ，針對(duì)numa架構(gòu)和sar成像處理的特點(diǎn)從加速比、編程復(fù)雜度等多個(gè)方面進(jìn)行了討論。
6. It's difficult to find matrix transpose in a sentence. 用matrix transpose造句挺難的
7. Chapter 2 analyzes parallel process technology ' s actuality , the requirement of real - time process , and mostly guidelines of parallel process performance . chapter 3 discusses imaging algorithm - - - - - - chirp scaling algorithm theory as well as realization of ideal point target ; and then discuss the scalar of data and operation . chapter 4 discuss the fft and distributed matrix transposing , mostly about ( 1 ) discussed how to realize parallel fft , and evaluate the preformance of parallel fft ; ( 2 ) discuss another step ' s - - - - - - matrix transposing - - - - - - realization can divided into three steps : distributing , renewedly distributing and local transposing of matrix , and then discuss the time of process in detail
   第四章分別研究了cs算法中的fft變換和分布式矩陣的轉(zhuǎn)置問(wèn)題，主要有： ( 1 )對(duì)cs算法中運(yùn)算量最大的步驟fft變換進(jìn)行了并行性的提取，并對(duì)并行fft變換的算法性能進(jìn)行了評(píng)估； ( 2 )分析并研究了cs算法中另一不可或缺的步驟? ?矩陣轉(zhuǎn)置問(wèn)題，提出矩陣分布、重新分布和局部轉(zhuǎn)置來(lái)實(shí)現(xiàn)矩陣轉(zhuǎn)置的并行化，并詳細(xì)分析了矩陣轉(zhuǎn)置的時(shí)間耗費(fèi)問(wèn)題。