fastDNAml is an attempt to solve the same problem as DNAML, but to do so faster and using less memory, so that larger trees and/or more bootstrap replicates become tractable. much of fastDNAml is merely a recoding of the PHYLIP 3.3 DNAML program from PASCAL to C.
標(biāo)簽： fastDNAml attempt problem faster
上傳時(shí)間： 2014-01-24
上傳用戶：bjgaofei
This PNG Delphi version 1.56 documentation (this version is a major rewrite intended to replace the previous version, 1.2). Improvements in this new version includes: This new version allows the programmer to not use Delphi heavy units which will greatly reduce the size of the final executable. Read more about this feature here. Most, if not all, Portable Network Graphics features as CRC checking are now fully performed. Error on broken images are now better handled using new exception classes. The images may be saved using interlaced mode also. Transparency information won t be discarted after the image is loaded any more. Most of the images are decoded much faster now. The images will be better encoded using fresh new algorithms. IMPORTANT! Now transparency information is used to display images.
標(biāo)簽： version documentation intended rewrite
上傳時(shí)間： 2015-06-28
上傳用戶：qiao8960
This book focuses on combining C++ s power and flexibility with high performance and scalability, resulting in the best of both worlds. Specific topics include temporary objects, memory management, templates, inheritance, virtual functions, inlining, referencecounting, STL, and much more
標(biāo)簽： flexibility performance scalability and
上傳時(shí)間： 2015-07-02
上傳用戶：784533221
good program ，I like very much
上傳時(shí)間： 2014-01-08
上傳用戶：lhc9102
he AVRcam source files were built using the WinAVR distribution (version 3.3.1 of GCC). I haven t tested other versions of GCC, but they should compile without too much difficulty. The makefile used to build the source is included
標(biāo)簽： distribution version AVRcam WinAVR
上傳時(shí)間： 2014-10-26
上傳用戶：h886166
College entrance examination management system has very big help to beginning to learn java language , the first time upload asks excuse me much
標(biāo)簽： examination management beginning entrance
上傳時(shí)間： 2015-08-20
上傳用戶：huannan88
Following is a repost of the public domain make that I posted to net.sources a couple of months ago. I have fixed a few bugs, and added some more features, and the resulting changes amounted to about as much text as the whole program (hence the repost).一個(gè)編譯器C代碼，詳見REDME。
標(biāo)簽： Following sources domain couple
上傳時(shí)間： 2015-09-01
上傳用戶：manlian
P2P (peer to peer) file sharing program in C#. Supports Gnutella, Gnutella2, eDonkey, and OpenNap. www.filescope.com. This is excellent for people wanting to learn socket programming, GUI effects via drawing, custom drawn controls (tabcontrol, menus, etc.), network transfers, and much more.
標(biāo)簽： Gnutella peer Supports OpenNap
上傳時(shí)間： 2015-10-01
上傳用戶：change0329
megahal is the conversation simulators conversing with a user in natural language. The program will exploit the fact that human beings tend to read much more meaning into what is said than is actually there MegaHAL differs from conversation simulators such as ELIZA in that it uses a Markov Model to learn how to hold a conversation. It is possible to teach MegaHAL to talk about new topics, and in different languages.
標(biāo)簽： conversation conversing simulators language
上傳時(shí)間： 2015-10-09
上傳用戶：lnnn30
Learning Kernel Classifiers: Theory and Algorithms, Introduction This chapter introduces the general problem of machine learning and how it relates to statistical inference. 1.1 The Learning Problem and (Statistical) Inference It was only a few years after the introduction of the first computer that one of man’s greatest dreams seemed to be realizable—artificial intelligence. Bearing in mind that in the early days the most powerful computers had much less computational power than a cell phone today, it comes as no surprise that much theoretical research on the potential of machines’ capabilities to learn took place at this time. This becomes a computational problem as soon as the dataset gets larger than a few hundred examples.
標(biāo)簽： Introduction Classifiers Algorithms introduces
上傳時(shí)間： 2015-10-20
上傳用戶：aeiouetla
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