The Rayleigh Integral Method is useful in computing the acoustic properties of a flat panel radiating into a half space.
标签： properties computing Rayleigh Integral
上传时间： 2015-12-07
上传用户：youmo81
celestia源代码，Celestia, a real-time 3D space simulation featuring a database of over 100000 stars, nearly a hundred solar system, objects, and a complete catalog of extrasolar planets.
上传时间： 2013-12-26
上传用户：缥缈
In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed.We showin particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.
标签： sequential simulation posterior overview
上传时间： 2015-12-31
上传用户：225588
To estimate the input-output mapping with inputs x ％ and outputs y generated by the following nonlinear, ％ nonstationary state space model: ％ x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)] ％ + 8cos(1.2t) + process noise ％ y(t) = x(t)^(2) / 20 + 6 squareWave(0.05(t-1)) + 3 ％ + time varying measurement noise ％ using a multi-layer perceptron (MLP) and both the EKF and ％ the hybrid importance-samping resampling (SIR) algorithm.
标签： input-output the generated following
上传时间： 2014-01-05
上传用户：royzhangsz
MSVM，svm的多分类问题实现，实现语言为c
标签： MSVM
上传时间： 2014-01-27
上传用户：evil
We have a group of N items (represented by integers from 1 to N), and we know that there is some total order defined for these items. You may assume that no two elements will be equal (for all a, b: a<b or b<a). However, it is expensive to compare two items. Your task is to make a number of comparisons, and then output the sorted order. The cost of determining if a < b is given by the bth integer of element a of costs (space delimited), which is the same as the ath integer of element b. Naturally, you will be judged on the total cost of the comparisons you make before outputting the sorted order. If your order is incorrect, you will receive a 0. Otherwise, your score will be opt/cost, where opt is the best cost anyone has achieved and cost is the total cost of the comparisons you make (so your score for a test case will be between 0 and 1). Your score for the problem will simply be the sum of your scores for the individual test cases.
标签： represented integers group items
上传时间： 2016-01-17
上传用户：jeffery
对应论文写的时空码的仿真程序。为2天线，BPSK调制模式。自己写的Space time code simulation提供给大家
上传时间： 2014-01-27
上传用户：Shaikh
OpenSVM was developped under Visual C++ 6.0 SP6, You can open the workspace file(*.dsw) in the opensvm-src folder. The folder include the svm.h and svm.cpp which in the libsvm (Copyright (c) 2000-2007 Chih-Chung Chang and Chih-Jen Lin All rights reserved) in the opensvm-src\libsvm. However, the files svm.h and svm.cpp codes were copied/merged into stdafx.h and stdafx.cpp in order to support the development, and OpenSVM still use other codes of libsvm. So you can see the libsvm package in the source package. You can open and build it with Visual C++ 6.0. Note: the problems must be in LIBSVM format. OpenSVM project page: http://sourceforge.net/projects/opensvm If you had any question, please mail to: cloudbyron@gmail.com
标签： developped the workspace OpenSVM
上传时间： 2016-01-30
上传用户：asdfasdfd
支持向量机导轮，让你对svm有更进一步的理解，
标签： 支持向量机
上传时间： 2016-02-04
上传用户：lhw888
本文的题目是改进的核函数算法及其在人脸识别中的应用研究。 本文在系统学习现有核函数及支持向量机相关理论的基础上，系统研究了自适应选择核函数算法，通过引入朴素正则风险最小化准则，提出了一种改进的在线核函数算法。算法采用截断误差最小化、合理选取拉格郎日因子等方法对新增样本进行训练，有效地克服了现有方法收敛精度低和不能自适应选择样本的困难。 根据独立分量分析的原理和特点，将改进的核函数算法引入人脸识别的研究中，给出了基于ICA-SVM的人脸识别算法及实现方法。 论文分别应用数值仿真及现有人脸数据库，分析了算法的数值特性并验证了算法的可靠性和实用性。 本文数值仿真与分析软件基于MATLAB和LABVIEW虚拟仪器设计开发。 本文档是nh文件，可以用caj打开。与大家共享！！
上传时间： 2016-02-14
上传用户：Divine
