Description: S-ISOMAP is a manifold learning algorithm, which is a supervised variant of ISOMAP. Reference: X. Geng, D.-C. Zhan, and Z.-H. Zhou. Supervised nonlinear dimensionality reduction for visualization and classification. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2005, vol.35, no.6, pp.1098-1107.
標(biāo)簽： Description supervised algorithm S-ISOMAP
上傳時間： 2015-04-10
上傳用戶：wfeel
· Develop clear, readable, well-documented and well-designed programs in the C Programming Language. · Develop software in the Unix/Linux using tools such as gcc, gdb, and make. · Locate and interpreting “man pages” applicable to application-level system programming. · Use the POSIX/Unix API to system functions to manage process and sessions as well as use signals and pipes for inter-process communication. · Understanding how synchronization might become problematic in light of concurrency. · Understand how to communicate and cooperate with a project partner.
標(biāo)簽： well-documented well-designed Programming Language
上傳時間： 2015-08-16
上傳用戶：yuchunhai1990
Learning Kernel Classifiers: Theory and Algorithms, Introduction This chapter introduces the general problem of machine learning and how it relates to statistical inference. 1.1 The Learning Problem and (Statistical) Inference It was only a few years after the introduction of the first computer that one of man’s greatest dreams seemed to be realizable—artificial intelligence. Bearing in mind that in the early days the most powerful computers had much less computational power than a cell phone today, it comes as no surprise that much theoretical research on the potential of machines’ capabilities to learn took place at this time. This becomes a computational problem as soon as the dataset gets larger than a few hundred examples.
標(biāo)簽： Introduction Classifiers Algorithms introduces
上傳時間： 2015-10-20
上傳用戶：aeiouetla
Linux C函數(shù)庫手冊和內(nèi)核分析方法，Linux程序員如果不喜歡用man的話就一定需要一本這樣的函數(shù)庫手冊
標(biāo)簽： Linux 函數(shù)庫 內(nèi)核
上傳時間： 2016-01-22
上傳用戶：924484786
This the third edition of the Writing Device Drivers articles. The first article helped to simply get you acquainted with device drivers and a simple framework for developing a device driver for NT. The second tutorial attempted to show to use IOCTLs and display what the memory layout of Windows NT is. In this edition, we will go into the idea of contexts and pools. The driver we write today will also be a little more interesting as it will allow two user mode applications to communicate with each other in a simple manner. We will call this the “poor man’s pipes” implementation.
標(biāo)簽： the articles Drivers edition
上傳時間： 2014-01-16
上傳用戶：ommshaggar
源碼，STR710，可發(fā)PWM，MAN，DIFMAN等編碼形式RF波形，送入TDA系列芯片調(diào)制發(fā)射
標(biāo)簽： 源碼
上傳時間： 2013-12-20
上傳用戶：風(fēng)之驕子
IEEE 802.11h-2003 IEEE Standard for Information technology—Telecommunications and Information Exchange Between Systems—LAN/MAN Specific Requirements—Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Spectrum and Transmit Power Management Extensions in the 5GHz band in Europe
標(biāo)簽： Information Telecommunications IEEE technology
上傳時間： 2016-10-02
上傳用戶：lnnn30
udp-cast!可以用multicasting的方式把檔案傳送到一個群組，很好用~~~~!有興趣的人式式吧。 1.先make 2.會產(chǎn)生兩個兩進(jìn)位檔，sender用來擴(kuò)播檔案 詳細(xì)就man udp-cast吧
標(biāo)簽： multicasting udp-cast 方式
上傳時間： 2013-12-26
上傳用戶：13215175592
LINUX下的C 函數(shù)查詢，有很多基本函數(shù)，但是最好的大家是參考MAN手冊。
上傳時間： 2017-03-16
上傳用戶：wfeel
OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.
標(biāo)簽： OTSU segmentation Gray-level segmented
上傳時間： 2017-04-24
上傳用戶：yuzsu
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