ComPort Library version2.62 for Delphi 3, 4, 5 and C++ Builder 3, 4, 5
標簽： ComPort Builder Library version
上傳時間： 2013-12-31
上傳用戶：zjf3110
PCI Specification version2.2
標簽： Specification Version PCI 2.2
上傳時間： 2015-02-23
上傳用戶：fanboynet
JavaServer Pages™ Specification version2.0---jsp的規范
標簽： Specification JavaServer Version Pages
上傳時間： 2015-09-29
上傳用戶：cxl274287265
混沌時間序列分析與預測工具箱 version2.0
上傳時間： 2016-06-03
上傳用戶：xuanjie
java servlet specification version2，全面系統介紹servlet的相關內容
標簽： specification version2 servlet java
上傳時間： 2014-09-02
上傳用戶：jkhjkh1982
matlab工具箱,使用有限元計算ODEs(常微分), PDEs(偏微分),BVPs(邊值問題),包括一維,二維,三維.(Matlab Finite Element toolbox,version2.01)
標簽： Element toolbox version matlab
上傳時間： 2017-04-21
上傳用戶：yzhl1988
On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標簽： demonstrates sequential Selection Bayesian
上傳時間： 2016-04-07
上傳用戶：lindor
This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標簽： sequential reversible algorithm nstrates
上傳時間： 2014-01-18
上傳用戶：康郎
1、該工具箱包括了混沌時間序列分析與預測的常用方法,有: (1)產生混沌時間序列(chaotic time series) Logistic映射 - \ChaosAttractors\Main_Logistic.m Henon映射 - \ChaosAttractors\Main_Henon.m Lorenz吸引子 - \ChaosAttractors\Main_Lorenz.m Duffing吸引子 - \ChaosAttractors\Main_Duffing.m Duffing2吸引子 - \ChaosAttractors\Main_Duffing2.m Rossler吸引子 -
標簽： matlab，GP，分維
上傳時間： 2015-03-02
上傳用戶：吳相澎peng
IEEE1149.1的產生1985年由IBM、AT&T、Texas Instruments、Philips Electronics NV、Siemens、Alcatel和Ericsson等公司成立的JETAG（Joint European Test Action Group）提出了邊界掃描技術。1986年由于其它地區的一些公司的加入，JETAG改名為JTAG。1988年JTAG提出了標準的邊界掃描體系結構，名稱叫Boundary-Scan Architecture Standard Proposal，version2.0，1990年IEEE正式承認了JTAG標準，經過補充和修訂以后命名命名為IEEE1149.1-90。同年又提出了BSDL（Boundary Scan Description Lauguage，邊界掃描描述語言）。后來成為IEEE1149.1-93標準的一部分。
標簽： jtag
上傳時間： 2022-07-06
上傳用戶：canderile
