提出了一種CPM信號Laurent分解和最小均方誤差檢測相結合的低復雜度接收機,在降低運算量的同時,保證了低信噪比情況下接近于最大似然ML、最優檢測器的接收機性能。理論推導和仿真結果均驗證了該算法的有效性。
上傳時間： 2013-11-15
上傳用戶：徐孺
This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equations are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the number of time samples and M the number of sources.
標簽： instantaneous algorithm Bayesian Gaussian
上傳時間： 2013-12-19
上傳用戶：jjj0202
Description: FASBIR(Filtered Attribute Subspace based Bagging with Injected Randomness) is a variant of Bagging algorithm, whose purpose is to improve accuracy of local learners, such as kNN, through multi-model perturbing ensemble. Reference: Z.-H. Zhou and Y. Yu. Ensembling local learners through multimodal perturbation. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2005, vol.35, no.4, pp.725-735.
標簽： Description Randomness Attribute Filtered
上傳時間： 2015-04-10
上傳用戶：ynzfm
WML（Wireless Markup Language - 無線標記語言）這種描述語言同我們常聽說的HTML語言同出一家，都屬于X ML語言這一大家族。HTML語言寫出的內容，我們可以在我們的PC機上用IE或是Netscape等瀏覽器進行閱讀，而 WML語言寫出的文件則是專門用來在手機等的一些無線終端顯示屏上顯示，供人們閱讀的，并且同樣也可以向使用者提供人機交互界面，接受使用者輸入的查詢等信息，然后向使用者返回他所想要獲得的最終信息。
標簽： Language Wireless Markup HTML
上傳時間： 2013-12-05
上傳用戶：csgcd001
IDCT-M is a medium speed 1D IDCT core -- it can accept a continous stream of 12-bit input words at a rate of -- 1 bit/ck cycle, operating at 50MHz speed, it can process MP@ML MPEG video -- the core is 100％ synthesizable
標簽： continous IDCT-M accept medium
上傳時間： 2015-07-07
上傳用戶：1583060504
供初學空時編碼（vblast接收）的matlab仿真程序，是關于vblast接收中ML算法的簡單的仿真
上傳時間： 2015-09-04
上傳用戶：diets
該程序模擬UNIX中save與resume函數,并介紹在VC中如何使用匯編進行機器級的操作. 主函數很簡單首先引入兩個外部函數,extern "C"表示按傳統C命名習慣.函數save將程序指針保存在(*s)中并返回0,為什么有 if(save(&sp)){...} if后的語句看起來永遠都不會被執行,但是運行結果表明它被執行了.這個問題同UNIX中處理機調度函數(switch)的那個if語句(第一句)一樣. 程序執行完save(&sp)后得到因為條件為假而執行else語句,卻在判斷之前將程序指針保存在sp中了. else語句中的resume(&sp),該函數很狡猾將堆棧中的返回地址改變了,改到了sp所指出,即將程序指針改到了執行條件判斷前.resume返回1,條件滿足,執行if語句. save函數堆棧: eip ebp+8 s ebp+4 ebp ebp+0 resume函數堆棧與save的相同. 新建一個win32的工程,將unixc.cpp和unix.obj加入過程即可. unix.obj是用masm6.11生成的:ml /c /coff unix.asm,生成coff格式的obj而不是omf格式.
上傳時間： 2015-09-10
上傳用戶：變形金剛
ApMl provides users with the ability to crawl the web and download pages to their computer in a directory structure suitable for a Machine Learning system to both train itself and classify new documents. Classification Algorithms include Naive Bayes, KNN
標簽： the provides computer download
上傳時間： 2015-11-29
上傳用戶：ywqaxiwang
Hidden_Markov_model_for_automatic_speech_recognition This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner (1) and others. Serious students are directed to the sources listed below for a theoretical description of the algorithm. KF Lee (2) offers an especially good tutorial of how to build a speech recognition system using hidden Markov models.
標簽： Hidden_Markov_model_for_automatic speech_recognition implements left-right
上傳時間： 2016-01-23
上傳用戶：569342831
一種常用空分復用的MIMO系統，v-blast系統的各種檢測算法：ML，MMSE,ZF,以及采用迫零的連續干擾消除檢測算法
上傳時間： 2013-12-13
上傳用戶：源弋弋
