This program demonstrates some function approximation capabilities of a Radial Basis Function Network. The user supplies a set of training points which represent some "sample" points for some arbitrary curve. Next, the user specifies the number of equally spaced gaussian centers and the variance for the network. Using the training Samples, the weights multiplying each of the gaussian basis functions arecalculated using the pseudo-inverse (yielding the minimum least-squares solution). The resulting network is then used to approximate the function between the given "sample" points.
標簽： approximation demonstrates capabilities Function
上傳時間： 2014-01-01
上傳用戶：zjf3110
function y_cum = cum2x (x,y, maxlag, nsamp, overlap, flag) ％CUM2X Cross-covariance ％ y_cum = cum2x (x,y,maxlag, samp_seg, overlap, flag) ％ x,y - data vectors/matrices with identical dimensions ％ if x,y are matrices, rather than vectors, columns are ％ assumed to correspond to independent realizations, ％ overlap is set to 0, and samp_seg to the row dimension. ％ maxlag - maximum lag to be computed [default = 0] ％ samp_seg - Samples per segment [default = data_length] ％ overlap - percentage overlap of segments [default = 0] ％ overlap is clipped to the allowed range of [0,99].
標簽： cum2x y_cum Cross-covariance function
上傳時間： 2015-09-08
上傳用戶：xieguodong1234
In this edition, the majority of the book is dedicated to covering the Winsock API. Chapter 1 starts with an introduction to Winsock and is specifically geared for the beginning Winsock programmer. This chapter covers all the basics and introduces Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) through simple Samples, as well as providing a roadmap to advanced Winsock topics covered in other chapters. For the sake of simplicity, Chapter 1 covers the IPv4 protocol.
標簽： the dedicated covering majority
上傳時間： 2015-09-08
上傳用戶：ommshaggar
This thorough, hands-on reference for database developers and administrators delivers expert guidance on sophisticated uses of Transact-SQL (T-SQL)¡ ª one of the most familiar and powerful programming languages for SQL Server. Written by a T-SQL guru, this guide focuses on language features and how they are interpreted and processed by the SQL Server execution engine. You¡ ¯ ll get in-depth coverage of the sophisticated uses of T-SQL, including triggers, user-defined functions, exception handling, and more. The book explains and compares solutions to database-development problems in both SQL Server 2000 and SQL Server 2005, discussing the new T-SQL programming features added to SQL Server 2005 in detail. Includes extensive code Samples, table examples, and logic puzzles to help database developers and administrators understand the intricacies and help promote mastery of T-SQL.
標簽： administrators developers reference thorough
上傳時間： 2013-12-29
上傳用戶：Avoid98
在pc 機的根目錄下建立minigui- free 目錄，將下載的源代碼包copy 到該目錄， 解壓縮，生成libminigui-1.3.3、minigui-res-1.3.3、mde-1.3.0、mg-Samples-1.3.1。 我在該目錄中建立nfsroot 目錄，用以存放生成的文件。
上傳時間： 2015-11-29
上傳用戶：lvzhr
Welcome to the Microsoft CRM 3.0 Software Development Kit (SDK). This SDK contains a wealth of resources, including code Samples, that are designed to help you build powerful vertical applications using the Microsoft CRM platform. It includes the following sections: 1 Server Programming Guide 2 Client Programming Guide 3 ISV Programming Guide 4 Report Writers Guide 5 Appendix A 6 Glossary –
標簽： Development Microsoft SDK Software
上傳時間： 2014-01-20
上傳用戶：zhichenglu
SharpZipLib之前叫做NZipLib，完全由 C# 開發的壓縮庫，支持Zip, GZip, Tar and BZip2 ，為2007年8月最新0852release版的源文件和文檔說明！ Changes for v0.85.2 release Minor tweaks for CF, ZipEntryFactory and ZipFile. Fix for zip testing and Zip64 local header patching. FastZip revamped to handle file attributes on extract + other fixes Null ref in path filter fixed. Extra data handling fixes Revamped build and conditional compilation handling Many bug fixes for Zip64. Minor improvements to C# Samples. ZIP-1341 Non ascii zip password handling fix. ZIP-355 Fix for zip compression problem at low levels
標簽： SharpZipLib NZipLib
上傳時間： 2015-12-11
上傳用戶：84425894
SharpZipLib之前叫做NZipLib，完全由 C# 開發的壓縮庫，支持Zip, GZip, Tar and BZip2 ，為2007年8月最新0852release版的代碼實例！ Changes for v0.85.2 release Minor tweaks for CF, ZipEntryFactory and ZipFile. Fix for zip testing and Zip64 local header patching. FastZip revamped to handle file attributes on extract + other fixes Null ref in path filter fixed. Extra data handling fixes Revamped build and conditional compilation handling Many bug fixes for Zip64. Minor improvements to C# Samples. ZIP-1341 Non ascii zip password handling fix. ZIP-355 Fix for zip compression problem at low levels
標簽： SharpZipLib NZipLib
上傳時間： 2015-12-11
上傳用戶：love_stanford
In addition to all the people who contributed to the first edition, we would like to thank the following individuals for their generous help in writing this edition. Very special thanks go to Jory Prather for verifying the code Samples as well as fixing them for consistency. Thanks to Dave Thaler, Brian Zill, and Rich Draves for clarifying our IPv6 questions, Mohammad Alam and Rajesh Peddibhotla for help with reliable multicasting, and Jeff Venable for his contributions on the Network Location Awareness functionality. Thanks to Vadim Eydelman for his Winsock expertise. And finally we would like to thank the .NET Application Frameworks team (Lance Olson, Mauro Ottaviani, and Ron Alberda) for their help with our questions about .NET Sockets.
標簽： the contributed addition to
上傳時間： 2015-12-17
上傳用戶：dongqiangqiang
We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of Samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers.
標簽： frequency-offset estimation quadrature amplitude
上傳時間： 2014-01-22
上傳用戶：牛布牛
