假定已經(jīng)有許多應(yīng)用采用了程序1 - 1 5中所定義的C u r r e n c y類，現(xiàn)在我們想要對(duì)C u r r e n c y類 的描述進(jìn)行修改，使其應(yīng)用頻率最高的兩個(gè)函數(shù)A d d和I n c r e m e n t可以運(yùn)行得更快，從而提高應(yīng) 用程序的執(zhí)行速度。由于用戶僅能通過p u b l i c部分所提供的接口與C u r r e n c y類進(jìn)行交互，
上傳時(shí)間： 2015-10-11
上傳用戶：BIBI
鄰接矩陣類的根是A d j a c e n c y W D i g r a p h，因此從這個(gè)類開始。程序1 2 - 1給出了類的描述。程 序中，先用程序1 - 1 3中函數(shù)Make2DArray 為二組數(shù)組a 分配空間，然后對(duì)數(shù)組a 初始化，以描述 一個(gè)n 頂點(diǎn)、沒有邊的圖的鄰接矩陣，其復(fù)雜性為( n2 )。該代碼沒有捕獲可能由M a k e 2 D A r r a y 引發(fā)的異常。在析構(gòu)函數(shù)中調(diào)用了程序1 - 1 4中的二維數(shù)組釋放函數(shù)D e l e t e 2 D
標(biāo)簽： 矩陣
上傳時(shí)間： 2013-12-21
上傳用戶：lanjisu111
第二個(gè)搜索函數(shù)為私有成員函數(shù)S a v e S e a r c h，由插入和刪除操作來(lái)調(diào)用。S a v e S e a r c h不僅 包含了S e a r c h的功能，而且可把每一級(jí)中遇到的最后一個(gè)節(jié)點(diǎn)存放在數(shù)組l a s t之中
上傳時(shí)間： 2015-10-11
上傳用戶：zm7516678
ICA MatLab Code from Appendix D代碼，或許對(duì)剛接觸BSS的有點(diǎn)用
標(biāo)簽： Appendix MatLab Code from
上傳時(shí)間： 2014-01-22
上傳用戶：LouieWu
ertfv ertt vweretv werf r
標(biāo)簽： vweretv ertfv ertt werf
上傳時(shí)間： 2015-10-15
上傳用戶：wanqunsheng
egdr grg g r dgr drg dgdr gdr gzdrg
上傳時(shí)間： 2015-10-19
上傳用戶：alan-ee
本程序是D.R.J.OWEN主編的FINITE ELEMENTS IN PLASTICITYG一書中第八章例題的有限元程序，網(wǎng)上流傳的這個(gè)版本的源碼里有錯(cuò)誤，我把它更正過來(lái)了，而且還添加了輸入文本。絕對(duì)好東西啊。
標(biāo)簽： PLASTICITYG ELEMENTS FINITE OWEN
上傳時(shí)間： 2014-01-23
上傳用戶：myworkpost
D.R.J.OWEN的經(jīng)典著作--< 有限元程序>
上傳時(shí)間： 2013-12-25
上傳用戶：dave520l
In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discrete-data linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation.
標(biāo)簽： R.E. discrete-dat describing published
上傳時(shí)間： 2015-10-22
上傳用戶：2404
In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata linear filtering problem [Kalman60]. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. A very “friendly” introduction to the general idea of the Kalman filter can be found in Chapter 1 of [Maybeck79], while a more complete introductory discussion can be found in [Sorenson70], which also contains some interesting historical narrative.
標(biāo)簽： R.E. discretedata describing published
上傳時(shí)間： 2015-10-22
上傳用戶：a673761058
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