This LDPC software is intended as an introduction to LDPC codes computer based simulation. The pseudo-random irregular low density parity check matrix is based on Radford M. Neal’s programs collection, which can be found in [1]. While Neal’s collection is well documented, in my opinion, C source codes are still overwhelming, especially if you are not knowledgeable in C language. My software is written for MATLAB, which is more readable than C. You may also want to refer to another MATLAB based LDPC source codes in [2], which has different flavor of code-writing style (in fact Arun has error in his log-likelihood decoder).
標簽： LDPC introduction simulation software
上傳時間： 2014-12-05
上傳用戶：change0329
A SoC-based Sensor Node 一篇國外最新的英文論文，對于用cc2430做無線傳感器網絡的研究，很有參考價值
上傳時間： 2016-06-10
上傳用戶：heart520beat
JSP Jsp tomcat is based on the framework javabean
標簽： framework javabean tomcat based
上傳時間： 2016-06-10
上傳用戶：xzt
獨立分量分析(Independent Component Analysis，簡稱ICA)是近二十年來逐漸發展起來的一種盲信號分離方法。它是一種統計方法，其目的是從由傳感器收集到的混合信號中分離出相互獨立的源信號，使得這些分離出來的源信號之間盡可能獨立。它在語音識別、電信和醫學信號處理等信號處理方面有著廣泛的應用，目前已成為盲信號處理，人工神經網絡等研究領域中的一個研究熱點。 本文簡要的闡述了ICA的發展、應用和現狀，詳細地論述了ICA的原理及實現過程，系統地介紹了目前幾種主要ICA算法以及它們之間的內在聯系，在此基礎上重點分析了一種快速ICA實現算法一FastICA。 物質的非線性熒光譜信號可以看成是由多個相互獨立的源信號組合成的混合信號，而這些獨立的源信號可以看成是光譜的特征信號。為了更好的了解光譜信號的特征，本文利用獨立分量分析的思想和方法，提出了利用FastICA算法提取光譜信號的特征的方案，并進行了仿真實驗。
標簽： Independent Component Analysis 分
上傳時間： 2013-12-20
上傳用戶：yan2267246
ASP.NET Ajax technologies based on the mail system
標簽： technologies system based Ajax
上傳時間： 2013-12-21
上傳用戶：zm7516678
一個基于Matlab的人工免疫算法％Immune Algorithm based on the immune network model for function f(x1,x2) optimum
標簽： Algorithm function network optimum
上傳時間： 2013-12-23
上傳用戶：changeboy
Face recognition based on PCA. A complete system and related introduction! Maybe it can help you!
標簽： introduction recognition complete related
上傳時間： 2016-06-23
上傳用戶：561596
pca人臉識別This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
標簽： implements Principal Component Analysis
上傳時間： 2014-01-03
上傳用戶：佳期如夢
PCA人臉識別 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
標簽： implements Component Principal Analysis
上傳時間： 2016-06-25
上傳用戶：trepb001
PCA人臉識別 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
標簽： implements Component Principal Analysis
上傳時間： 2016-06-25
上傳用戶：hakim
