AT91SAM7SE512 Boundary-Scan Description files (BSD)for LQFP 128 and LFBGA 144 packages.
標簽： Boundary-Scan Description packages LFBGA
上傳時間： 2016-04-03
上傳用戶：zhliu007
AT91SAM7S64_TQ64_bsd.zip Boundary-Scan Description file (BSD) for the AT91SAM7S64 in LQFP 64 package.
標簽： 64 Boundary-Scan Description SAM
上傳時間： 2013-12-19
上傳用戶：hasan2015
AT91SAM7S256_TQ64_bsd.zip Boundary-Scan Description file (BSD) for the AT91SAM7S256 in LQFP 64 package.
標簽： Boundary-Scan Description 256 SAM
上傳時間： 2013-12-18
上傳用戶：libenshu01
最大李雅普諾夫指數的計算 該函數用來計算時間序列的最大Lyapunov 指數--Wolf 方法 ％ m: 嵌入維數 ％ tau:時間延遲 ％ data:時間序列 ％ N:時間序列長度 ％ P:時間序列的平均周期,選擇演化相點距當前點的位置差，即若當前相點為I，則演化相點只能在|I－J|>P的相點中搜尋
上傳時間： 2013-12-10
上傳用戶：hewenzhi
快跳頻通信畢業論文 含ppt幻燈、m仿真、doc論文
上傳時間： 2013-12-31
上傳用戶：Pzj
Gold序列是基于m序列優選對產生的，是由兩個長度相同、速率相同、但碼字不同的m序列優選對模2加后得到的，一對長度為N的m序列優選對可以產生N＋2條Gold碼。
上傳時間： 2016-04-10
上傳用戶：lingzhichao
用于DVB的OFDM源代碼.包含代碼DVB_T2Ksignalgeneration.m OFDMReception.m OFDMTransmission.m等
標簽： Ksignalgeneration OFDMTransmission OFDMReception DVB_T
上傳時間： 2016-04-10
上傳用戶：小草123
IMM_Kalman_Filter.m IMM_Kalman_Filter程序
標簽： IMM_Kalman_Filter 程序
上傳時間： 2013-12-13
上傳用戶：xmsmh
Pixel Labeled Algorithm Based on Recursive M ethod of Connecting Area in Binary Images
標簽： Connecting Algorithm Recursive Labeled
上傳時間： 2013-12-08
上傳用戶：refent
In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
標簽： Rauch-Tung-Striebel algorithm smoother which
上傳時間： 2016-04-15
上傳用戶：zhenyushaw
