<pre id="soyaw"></pre> These instances, whenmapped to an N-dimensional space, represent a core set that can be used to construct an approximation to theminimumenclosing ball. Solving the SVMlearning problem on these core sets can produce a good approximation solution in very fast speed. For example, the core-vector MacHINe [81] thus produced can learn an SVM for millions of data in seconds.
標(biāo)簽： N-dimensional whenmapped instances represent
上傳時(shí)間： 2016-11-23
上傳用戶：lixinxiang
Many of the pattern fi nding algorithms such as decision tree, classifi cation rules and clustering techniques that are frequently used in data mining have been developed in MacHINe learning research community. Frequent pattern and association rule mining is one of the few excep- tions to this tradition. The introduction of this technique boosted data mining research and its impact is tremendous. The algorithm is quite simple and easy to implement. Experimenting with Apriori-like algorithm is the fi rst thing that data miners try to do.
標(biāo)簽： 64257 algorithms decision pattern
上傳時(shí)間： 2014-01-12
上傳用戶：wangdean1101
Semantic analysis of multimedia content is an on going research area that has gained a lot of attention over the last few years. Additionally, MacHINe learning techniques are widely used for multimedia analysis with great success. This work presents a combined approach to semantic adaptation of neural network classifiers in multimedia framework. It is based on a fuzzy reasoning engine which is able to evaluate the outputs and the confidence levels of the neural network classifier, using a knowledge base. Improved image segmentation results are obtained, which are used for adaptation of the network classifier, further increasing its ability to provide accurate classification of the specific content.
標(biāo)簽： multimedia Semantic analysis research
上傳時(shí)間： 2016-11-24
上傳用戶：蟲蟲蟲蟲蟲蟲
The VGA example generates a 320x240 diffusion-limited-aggregation (DLA) on Altera DE2 board. A DLA is a clump formed by sticky particles adhering to an existing structure. In this design, we start with one pixel at the center of the screen and allow a random walker to bounce around the screen until it hits the pixel at the center. It then sticks and a new walker is started randomly at one of the 4 corners of the screen. The random number generators for x and y steps are XOR feedback shift registers (see also Hamblen, Appendix A). The VGA driver, PLL, and reset controller from the DE2 CDROM are necessary to compile this example. Note that you must push KEY0 to start the state MacHINe.
標(biāo)簽： diffusion-limited-aggregation DLA generates 320x240
上傳時(shí)間： 2014-01-16
上傳用戶：225588
The literature of cryptography has a curious history. Secrecy, of course, has always played a central role, but until the First World War, important developments appeared in print in a more or less timely fashion and the field moved forward in much the same way as other specialized disciplines. As late as 1918, one of the most influential cryptanalytic papers of the twentieth century, William F. Friedman’s monograph The Index of Coincidence and Its Applications in Cryptography, appeared as a research report of the private Riverbank Laboratories [577]. And this, despite the fact that the work had been done as part of the war effort. In the same year Edward H. Hebern of Oakland, California filed the first patent for a rotor MacHINe [710], the device destined to be a mainstay of military cryptography for nearly 50 years.
標(biāo)簽： cryptography literature has Secrecy
上傳時(shí)間： 2016-12-08
上傳用戶：fxf126@126.com
虛擬機(jī)設(shè)計(jì)與實(shí)現(xiàn)——C/C++，即Virtual MacHINe Design and Implementation in C/C++ ，隨書光盤源碼，HEC虛擬機(jī)的源代碼
標(biāo)簽： 虛擬機(jī)
上傳時(shí)間： 2016-12-22
上傳用戶：洛木卓
數(shù)據(jù)加密算法（Data Encryption Algorithm，DEA）的數(shù)據(jù)加密標(biāo)準(zhǔn)（Data Encryption Standard，DES）是規(guī)范的描述，它出自 IBM 的研究工作，并在 1997 年被美國政府正式采納。它很可能是使用最廣泛的秘鑰系統(tǒng)，特別是在保護(hù)金融數(shù)據(jù)的安全中，最初開發(fā)的 DES 是嵌入硬 件中的。通常，自動(dòng)取款機(jī)（Automated Teller MacHINe，ATM）都使用 DES。文件是DES代碼的VHDL描述
標(biāo)簽： Encryption Algorithm Data 數(shù)據(jù)加密
上傳時(shí)間： 2014-09-07
上傳用戶：ztj182002
state of art language modeling methods: An Empirical Study of Smoothing Techniques for Language Modeling.pdf BLEU, a Method for Automatic Evaluation of MacHINe Translation.pdf Class-based n-gram models of natural language.pdf Distributed Language Modeling for N-best List Re-ranking.pdf Distributed Word Clustering for Large Scale Class-Based Language Modeling in.pdf
標(biāo)簽： Techniques Empirical Smoothing Language
上傳時(shí)間： 2016-12-26
上傳用戶：zhuoying119
基于C++闡述虛擬機(jī)編程原理 This guide provides an in-depth look at the construction and underlying theory of a fully functional virtual MacHINe and an entire suite of related development tools.
標(biāo)簽： construction underlying provides in-depth
上傳時(shí)間： 2017-02-12
上傳用戶：nanxia
In this paper, we describe the development of a rapidly reconfigurable system in which the users’ tacit knowledge and requirements are elicited via a process of Interactive Evolution, finding the image processing parameters to achieve the required goals without any need for specialised knowledge of the MacHINe vision system. We show that the resulting segmentation can be quickly and easily evolved from scratch, and achieves detection rates comparable to those of a hand-tuned system on a hot-rolled steel defect recognition problem.
標(biāo)簽： reconfigurable development the describe
上傳時(shí)間： 2014-01-05
上傳用戶：hopy
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