Random matrix theory - for communication systems.
標(biāo)簽： communication systems Random matrix
上傳時(shí)間： 2014-01-06
上傳用戶：ANRAN
a chap 2 for learn ing about java, it is a good for begineer start from learning for java
標(biāo)簽： for java begineer learning
上傳時(shí)間： 2014-01-10
上傳用戶：evil
a chap 315 updated for learn ing about java, it is a good for begineer start from learning for java
標(biāo)簽： for java begineer learning
上傳時(shí)間： 2015-08-23
上傳用戶：思琦琦
The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller(FCMAC) is proposed to control this cable compensation system. In FCMAC ,without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective.
標(biāo)簽： system compensation simulations experiment
上傳時(shí)間： 2015-08-26
上傳用戶：希醬大魔王
算法實(shí)現(xiàn):Jieping Ye. Generalized low rank approximations of matrices. Machine Learning, Vol. 61, pp. 167-191, 2005.
標(biāo)簽： approximations Generalized Learning matrices
上傳時(shí)間： 2015-08-29
上傳用戶：invtnewer
The third edition of Learning GNU Emacs describes Emacs 21.3 from the ground up, including new user interface features such as an icon-based toolbar and an interactive interface to Emacs customization. A new chapter details how to install and run Emacs on Mac OS X, Windows, and Linux, including tips for using Emacs effectively on those platforms.
標(biāo)簽： Emacs describes including Learning
上傳時(shí)間： 2015-08-29
上傳用戶：caixiaoxu26
LVQ算法( Learning Vector Quantization，學(xué)習(xí)矢量量化網(wǎng)絡(luò))是一種基于模型（神經(jīng)網(wǎng)絡(luò)）的方法，本實(shí)驗(yàn)要實(shí)現(xiàn)的是對LVQ改進(jìn)的聚類方法——MLVQ（閆德勤等人提出）。該方法克服了LVQ算法對初值敏感的問題和廣義學(xué)習(xí)矢量量化(GLVQ)網(wǎng)絡(luò)算法性能不穩(wěn)定的缺點(diǎn)。(附文章)
標(biāo)簽： Quantization Learning Vector LVQ
上傳時(shí)間： 2015-08-31
上傳用戶：youke111
This text introduces the spirit and theory of hacking as well as the science behind it all it also provides some core techniques and tricks of hacking so you can think like a hacker, write your own hacks or thwart potential system attacks. 譯作：《黑客入侵的藝術(shù)》，也是從朋友的寶箱中搜來的，以前層大致瀏覽過，是難得一件的好資料。
標(biāo)簽： introduces the hacking science
上傳時(shí)間： 2013-12-28
上傳用戶：離殤
gragh theory 很好的英文原版書，from bondy, 對喜歡編游戲的朋友有幫助
上傳時(shí)間： 2014-11-22
上傳用戶：xz85592677
2005 Center for Biological & Computational Learning at MIT and MIT All rights reserved. Permission to copy and modify this data, software, and its documentation only for internal research use in your organization is hereby granted, provided that this notice is retained thereon and on all copies. This data and software should not be distributed to anyone outside of your organization without explicit written authorization by the author(s) and MIT.
標(biāo)簽： Computational Biological MIT Permissio
上傳時(shí)間： 2014-01-27
上傳用戶：gaome
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