The Little Green BATS is the first and so far only Dutch team in the 3D simulation league. We are a group of graduate students from the department of AI at the University of Groningen, The Netherlands. Our team name is derived from the fact that the first 3D agents in the league were balls and from the very philosophical observation that Balls Are Truly Spheres (BATS). This abbreviation reminded us of our favorite song Little Green Bag by The George Baker Selection and so the whole team name was born. We entered the competition for the first time at the 10th edition of RoboCup at Bremen, Germany. unfortunately our hard work didn t pay off that time: already in the second round we got eliminated. However, after this we had a good base to build upon and the good time we had at the event and the nice community inspired us to continue and work hard for ANother year. This turned out to be defiantly worth it, because in 2007 in Atlanta we managed to become vice world champions!
標(biāo)簽： simulation the Little league
上傳時間： 2014-12-07
上傳用戶：youlongjian0
Flash中內(nèi)置了一個狀態(tài)寄存器（Status Register，SR）來指示Flash的當(dāng)前工作狀態(tài)和各種操作是否成功。要讀取SR的當(dāng)前值需要向CUI發(fā)送讀狀態(tài)寄存器命令（Read Status Register），命令碼為0x70，SR中的內(nèi)容將在DQ[7:0]上輸出。The Read Status Register （0x70）command causes subsequent reads to output data from the SR until ANother command is issued. The SR bits are output on DQ[7:0].
標(biāo)簽： Register Status Flash 內(nèi)置
上傳時間： 2016-08-12
上傳用戶：thesk123
xl2tpd is an implementation of the Layer 2 Tunnelling Protocol (RFC 2661). L2TP allows you to tunnel PPP over UDP. Some ISPs use L2TP to tunnel user sessions from dial-in servers (modem banks, ADSL DSLAMs) to back-end PPP servers. ANother important application is Virtual Private Networks where the IPsec protocol is used to secure the L2TP connection (L2TP/IPsec, RFC 3193). The L2TP/IPsec protocol is mainly used by Windows and Mac OS X clients. On Linux, xl2tpd can be used in combination with IPsec implementations such as Openswan.
標(biāo)簽： implementation Tunnelling Protocol xl2tpd
上傳時間： 2014-01-20
上傳用戶：Altman
The toolbox solves a variety of approximate modeling problems for linear static models. The model can be parameterized in kernel, image, or input/output form and the approximation criterion, called misfit, is a weighted norm between the given data and data that is consistent with the model. There are three main classes of functions in the toolbox: transformation functions, misfit computation functions, and approximation functions. The approximation functions derive an approximate model from data, the misfit computation functions are used for validation and comparison of models, and the transformation functions are used for deriving one model representation from ANother. KEYWORDS: Total least squares, generalized total least squares, software implementation.
標(biāo)簽： approximate The modeling problems
上傳時間： 2013-12-20
上傳用戶：15071087253
an approach for capturing similarity between words that was concerned with the syntactic similarity of two strings. Today we are back to discuss ANother approach that is more concerned with the meaning of words. Semantic similarity is a confidence score that reflects the semantic relation between the meanings of two sentences. It is difficult to gain a high accuracy score because the exact semantic meanings are completely understood only in a particular context.
標(biāo)簽： similarity capturing concerned syntactic
上傳時間： 2014-01-05
上傳用戶：wmwai1314
In the previous article, we presented an approach for capturing similarity between words that was concerned with the syntactic similarity of two strings. Today we are back to discuss ANother approach that is more concerned with the meaning of words. Semantic similarity is a confidence score that reflects the semantic relation between the meanings of two sentences. It is difficult to gain a high accuracy score because the exact semantic meanings are completely understood only in a particular context.
標(biāo)簽： similarity presented capturing previous
上傳時間： 2013-12-13
上傳用戶：wcl168881111111
This manual documents the interfaces of the libxml library and has some short notes to help get you up to speed with using the library. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided also that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into ANother language, under the above conditions for modified versions.
標(biāo)簽： interfaces documents the library
上傳時間： 2016-11-08
上傳用戶：181992417
開源的項目哦，自制LED游戲機(jī) (ANother LED Game)
上傳時間： 2014-01-19
上傳用戶：tyler
Purpose: --- -- This component is used for capturing staff from AVI to BMP. Installation: ------------- Extract the compiled units into your Lib directory or into ANother directory that is listed in the Library path in your Delphi options. Choose file AVIcap.dcu for register. description: ------------ AVIcap V2.0 used for capturing frame from AVI without drawing on the screen, that is essentially fast. It can be reached by using of avifil32.dll from MS Video For Windows. New property: number of bits per pixel of bitmap.Now you can save BMP using next formats: pf1bit, pf4bit, pf8bit, pf8bitGray, pf15bit, pf16bit, pf24bit, pf32bit, pfDevice. See example to detail.
標(biāo)簽： Installation component capturing Purpose
上傳時間： 2016-12-13
上傳用戶：TF2015
neural network utility is a Neural Networks library for the C++ Programmer. It is entirely object oriented and focuses on reducing tedious and confusing problems of programming neural networks. By this I mean that network layers are easily defined. An entire multi-layer network can be created in a few lines, and trained with two functions. Layers can be connected to one ANother easily and painlessly.
標(biāo)簽： Programmer Networks entirely network
上傳時間： 2013-12-24
上傳用戶：liuchee
蟲蟲下載站版權(quán)所有 京ICP備2021023401號-1
