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www.eeworm.com/read/115326/15018041
c trianglemanuel.c
/*
1995-96 ACM International Collegiate Programming Contest
Southwestern European Regional Contest
ETH Zurich, Switzerland
December 9, 1995
Problem: Triangle
Idea and first implementation: Berni S
www.eeworm.com/read/115326/15018045
c intersectionmanuel.c
/*
ACM International Collegiate Programming Contest
1995-96 Southwestern European Regional Contest
ETH Zurich, Switzerland
Decmeber 9, 1995
Problem: Intersection
Idea: Andrea Kennel, ETH Zurich
www.eeworm.com/read/216268/15021371
m pr3_26.m
%Problem 3.26;
%Simulates antijamming features of spread spectrum signal (band elimination used) against narrow
%band jammer and compares to the ones of plain signals;
clear all; close all;
t=[0
www.eeworm.com/read/216268/15021375
m pr3_25.m
%Problem3.25
%Simulates antijamming features of spread spectrum signal (no band elimination used) against narrow
%band jammer and compares to the ones of plain signals;
clear all; close all;
t=[
www.eeworm.com/read/214167/15112307
cpp prg15_5.cpp
// File: prg15_5.cpp
// the program demonstrates the dynamic programming solution
// to the knapsack problem. the vector itemList contains
// five items, each with a specified size and value. after
www.eeworm.com/read/213492/15133769
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/213424/15135078
m bookdemo.m
% PURPOSE : We address here a nonlinear non-Gaussian problem using
% the standard particle filtering algorithm.
% For more details refer to the introduction of our book:
% Sequential Monte Carlo in P
www.eeworm.com/read/212602/15152042
m fm_opfsdr.m
function fm_opfsdr
%FM_OPFSDR solve the OPF-based electricity market problem by means of
% an Interior Point Method with a Merhotra Predictor-Corrector
% or Newton direction techniq
www.eeworm.com/read/212307/15160066
m demhmc1.m
%DEMHMC1 Demonstrate Hybrid Monte Carlo sampling on mixture of two Gaussians.
%
% Description
% The problem consists of generating data from a mixture of two
% Gaussians in two dimensions using a hybr
www.eeworm.com/read/212307/15160068
m demkmn1.m
%DEMKMEAN Demonstrate simple clustering model trained with K-means.
%
% Description
% The problem consists of data in a two-dimensional space. The data is
% drawn from three spherical Gaussian distri