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www.eeworm.com/read/138798/13212128
m demhmc2.m
%DEMHMC2 Demonstrate Bayesian regression with Hybrid Monte Carlo sampling.
%
% Description
% The problem consists of one input variable X and one target variable
% T with data generated by samplin
www.eeworm.com/read/138798/13212409
m demmlp2.m
%DEMMLP2 Demonstrate simple classification using a multi-layer perceptron
%
% Description
% The problem consists of input data in two dimensions drawn from a
% mixture of three Gaussians: two of w
www.eeworm.com/read/323353/13343219
java main.java
/**
*
*/
package problem8_3;
/**
* @author Administrator
*
*/
public class Main {
/**
* @param args
*/
public static void main(String[] args) {
// TODO 自动生成方法存根
StrAr
www.eeworm.com/read/321185/13411047
todo
TODO
====
- build date is not localized. [ao]
- check our current usage of the gettext tools [sf, mg]
PROBLEM: how do we may correctly differentiate between
versions of gettext with and without
www.eeworm.com/read/319487/13450571
cc ch4iter.cc
// chapter 3, section 1, computer problem 1: Bisection Method
// NUMERICAL ANALYSIS: MATHEMATICS OF SCIENTIFIC COMPUTING, SECOND EDITION
// David Kincaid & Ward Cheney, Brooks/Cole Publishing Co.,
www.eeworm.com/read/318840/13471274
m shootout.m
% Square root covariance filtering "shootout" on an
% ill conditioned problem from P. Dyer & S. McReynolds,
% "Extension of square-root filtering to include process noise"
% Journal of Optimization
www.eeworm.com/read/314385/13568733
m shootout.m
% Square root covariance filtering "shootout" on an
% ill conditioned problem from P. Dyer & S. McReynolds,
% "Extension of square-root filtering to include process noise"
% Journal of Optimization
www.eeworm.com/read/313956/13577976
m ip_09_05.m
% MATLAB script for Illustrative Problem 5, Chapter 9.
echo on
% first determine the maximal length shift register sequences
% We'll take the initial shift register content as "00001".
connections
www.eeworm.com/read/312163/13617540
m tune_ocr.m
% TUNE_OCR Tunes SVM classifier for OCR problem.
%
% Description:
% The following steps are performed:
% - Training set is created from data in directory ExamplesDir.
% - Multi-class SVM is
www.eeworm.com/read/309190/13679385
m lms3.m
%LMS3 Problem 1.1.1.2.1
%
% 'ifile.mat' - input file containing:
% I - members of ensemble
% K - iterations
% a1 - coefficient of input AR process
% sigmax - standard dev