【书名】非线性时间序列分析 【原 书 名】 Nonlinear Time Series Analysis 【原出版社】 Cambridge University Press 【作 者】Holger Kantz,Thomas Schreiber [同作者作品] 【丛 书 名】 剑桥非线性科学系列 【出 版 社】 清华大学出版社 【书 号】 7302039062 【出版日期】 2001 年3月 【开 本】 16开 【页 码】 304 【版 次】1-3
标签： University Nonlinear Cambridge Analysis
上传时间： 2013-12-27
上传用户：as275944189
Signal Processing and Linear Systems,B.P. Lathi,Berkeley-Cambridge Press book matlab codes
标签： Berkeley-Cambridge Processing Systems Signal
上传时间： 2017-06-01
上传用户：541657925
USB接口控制器参考设计,xilinx提供VHDL代码 usb xilinx vhdl ; This program is free software; you can redistribute it and/or modify ; it under the terms of the GNU General Public License as published by ; the Free Software Foundation; either version 2 of the License, or ; (at your option) any later version. ; ; This program is distributed in the hope that it will be useful, ; but WITHOUT ANY WARRANTY; without even the implied warranty of ; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ; GNU General Public License for more details. ; ; You should have received a copy of the GNU General Public License ; along with this program; if not, write to the Free Software ; Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
上传时间： 2013-10-12
上传用户：windgate
USB接口控制器参考设计,xilinx提供VHDL代码 usb xilinx vhdl ; This program is free software; you can redistribute it and/or modify ; it under the terms of the GNU General Public License as published by ; the Free Software Foundation; either version 2 of the License, or ; (at your option) any later version. ; ; This program is distributed in the hope that it will be useful, ; but WITHOUT ANY WARRANTY; without even the implied warranty of ; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ; GNU General Public License for more details. ; ; You should have received a copy of the GNU General Public License ; along with this program; if not, write to the Free Software ; Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
上传时间： 2013-10-28
上传用户：zhouchang199
最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast training of support vector machines using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the Generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999.
上传时间： 2013-12-16
上传用户：亚亚娟娟123
Hidden Markov Toolkit (HTK) 3.2.1 HTK is a toolkit for use in research into automatic speech recognition and has been developed by the Speech Vision Robotics Group at the Cambridge University Engineering Department (http://svr-www.eng.cam.ac.uk) and Entropic Ltd (http://www.entropic.com).
标签： HTK automatic research Toolkit
上传时间： 2015-05-26
上传用户：myworkpost
学生信息管理系统 GNU通用公共许可证 第二版，1991年 版权所有（C）1989，1991 Free Software foundation, Inc. 675 Mass Ave, Cambridge, MA02139, USA 允许每个人复制和发布这一许可证原始文档的副本，但绝对不允许对它进行任何修改。 序言 大多数软件许可证决意剥夺你的共享和修改软件的自由。对比之下，GNU通用公共许可证力图保证你的共享和修改自由软件的自由。——保证自由软件对所有用户是自由的。GPL适用于大多数自由软件基金会的软件，以及由使用这些软件而承担义务的作者所开发的软件。（自由软件基金会的其他一些软件受GNU库通用许可证的保护）。你也可以将它用到你的程序中。 当我们谈到自由软件（free software）时，我们指的是自由而不是价格。我们的GNU通用公共许可证决意保证你有发布自由软件的自由（如果你愿意，你可以对此项服务收取一定的费用）；保证你能收到源程序或者在你需要时能得到它；保证你能修改软件或将它的一部分用于新的自由软件；而且还保证你知道你能做这些事情。 为了保护你的权利，我们需要作出规定：禁止任何人不承认你的权利，或者要求你放弃这些权利。如果你修改了自由软件或者发布了软件的副本，这些规定就转化为你的责任。 例如
上传时间： 2013-12-21
上传用户：zuozuo1215
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.
标签： demonstrates sequential Selection Bayesian
上传时间： 2016-04-06
上传用户：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.
标签： sequential reversible algorithm nstrates
上传时间： 2014-01-18
上传用户：康郎
This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
标签： reversible algorithm the nstrates
上传时间： 2014-01-08
上传用户：cuibaigao
