OFDM based on the massive pilot channel estimation algorithm simulation, including the LS estimation algorithm analysis of LSE
标签： estimation simulation algorithm including
上传时间： 2017-03-28
上传用户：wpwpwlxwlx
it is the matlab implementation of CDMA2009 for the AWGN noise source crack for all the matter in the analysis
标签： the implementation for matlab
上传时间： 2017-03-29
上传用户：han_zh
Advanced ASIC Chip Synthesis Using Synopsys Design Compiler. This second edition of this book describes the advanced concepts and techniques used towards ASIC chip synthesis, physical synthesis, formal verification and static timing analysis, using the Synopsys suite of tools.
标签： Synthesis Advanced Synopsys Compiler
上传时间： 2017-04-04
上传用户：lanwei
1.an fpga implementation of the image space reconstruction algorithm for hyperspectral imaging analysis 2. fpga implemention of a median filter 3. fpga implementation of digital filters 4.hardware acceleration of edge detection algorithm on fpgas 5.implementation and evaluation of image processing algorithms on reconfigurable architecture using C-based hardware descriptive languages 6. implementing 2D median filter in fpgas 7.视频图像处理与分析的网络资源
标签： implementation reconstruction hyperspectral algorithm
上传时间： 2014-01-10
上传用户：894898248
网页采集系统 ================= 安装配置 ------- 1 程序我就不说了 2 配置文件 applicationContext.xml 里面有详细的注释 3 已经包含了多个论坛博客的参数，如CSDN论坛、博客园、新浪博客、百度Hi、ccidnet等的解析参数 需要的类库 --------- 1 Spring 2.5 2 common-logging 1.1 3 paoding-analysis 2.0.4-beta 4 commons-dbcp-1.2.2.jar 5 mysql-connector-java-5.1.7-bin.jar 6 commons-pool-1.4.jar 7 Lucene.2.4.0.jar 8 Lucene-highlighter-2.4.0.jar 9 java2000.jar 演示例子 ------- 本地：在com.laozizhu.search.demo目录下面 B/S: http://search.laozizhu.com
标签： applicationContext xml 页 采集系统
上传时间： 2017-04-07
上传用户：牧羊人8920
统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，analysis of linear discriminant function 2，Feature extraction: Linear Discriminant analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines
标签： Statistical Recognition Pattern Toolbox
上传时间： 2014-01-03
上传用户：璇珠官人
The philosophy of the book is to present various pattern recognition tasks in a unified way, including image analysis, speech processing, and communication applications. Despite their differences, these areas do share common features and their study can only benefit from a unified approach.
标签： recognition philosophy pattern present
上传时间： 2017-05-05
上传用户：plsee
In the last decade the processing of polygonal meshes has emerged as an active and very productive research area. This can basically be attributed to two developments: Modern geometry acquisition devices, like laser scanners and MRT, easily produce raw polygonal meshes of ever growing complexity Downstream applications like analysis tools (medical imaging), computer aided manufacturing, or numerical simulations all require high quality polygonal meshes as input. The need to bridge the gap between raw triangle soup data and high-quality polygon meshes has driven the research on ecient data structures and algorithms that directly operate on polygonal meshes rather than on a (most often not feasible) intermediate CAD representation.
标签： processing productive the polygonal
上传时间： 2017-06-03
上传用户：TF2015
The most straightforward approximation is the standard Gaussian approximation, where the MAI is approximated by a Gaussian random variable. This approximation is simple, however it is not accurate in general. In situations where the number of users is not large, the Gaussian approximation is not appropriate. In-depth analysis of must be applied. The Holtzman?s improved Gaussian approximation provides a better approximation to the MAI term. The approximation conditions the interference term on the operation condition of each user.
标签： approximation straightforward the Gaussian
上传时间： 2017-06-03
上传用户：dyctj
The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local memory-based models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.
标签： foundations The consists sections
上传时间： 2017-06-22
上传用户：lps11188
