caiorss

caiorss

% Filters the signal using coefficients obtained by the butter filter
% design
x_filtered = filter(b,a,y);

% Plots the filtered signal
figure(4)
plot(t,x_filtered,'r')
hold on 
plot(t,y0,'k','LineWidth',2)
hold on 

caiorss

%% Filter Design

% Designs a second order filter using a butterworth design guidelines
[b a] = butter(2,0.2,'high');

% Plot the frequency response (normalized frequency)
figure(3)
H = freqz(b,a,floor(num_bins/2));
plot(0:1/(num_bins/2 -1):1, abs(H), 'r');
hold on

caiorss

function stupid_tricks

    % I made some functional tools for MATLAB.
    assert(reduce_(@(x, y) x + y, [1, 2, 3, 4]) == 10)

    % They got a little out of hand.
    join = @(sep, args) ...
        if_(ischar(sep), @() ... % Input check
            reduce_(@(x, y) [x sep y], ... % Reduce to string
                map_(@num2str, args))); % Convert args to string.

caiorss

t = 0:0.001:1000;
x = cos(t);
y = sin(t);

fig = figure();
ax = axes();
hold on
dot1 = plot(x(1), y(1));
dot2 = plot(1.5 * x(1), 1.5 * y(2));
hold off

caiorss

%% Matlab-Skript zur Vorlesung Informationsuebertragung am 14.11.2014
% Autor: Valentin Burger, Michael Seufert, Steffen Gebert

clear all; %set(0, 'defaultlinelinewidth', 1);
figure(1);clf;box on;
A=5;                        % Amplitude
w=4;                        % Frequenz
phi=pi/2;                   % Phasenverschiebung
x=(0:0.001:2)*pi;
y=A*sin(x*w+phi);

caiorss

%Function lda takes in a list of Words and documents and generates the
%probability matrices for LDA
% INPUTS:
% W -list of words
% D -list of documents assigned to each word
% nTopics - number of topics to use for LDA
% maxIter - maximum iterations to run LDA
% nVocab - (optional) number of unique words
%
% Outputs:

caiorss

clear all
% Sample kinematic data set
% saved as TEST.m

% kinetic data from pg 191
% Reaction forces (RD from frame 7)  and Moment forces (M from frame 7)
RD7 = [-134.33 -768.38 -10.26]; % units are Newtons in GRS
MD7 = [16.13 -0.49 -101.32]  ;   % units are Newtons*meters in GRS
% RP7 = [-96.41 -755.17 -13.15]; % proximal reaction force used in the g to a axes system 
% kinetic data 'table 7.4' Leg angular displacements

caiorss

n = 20; % number of points
points = [random('unid', 100, n, 1), random('unid', 100, n, 1)];
len = zeros(1, n - 1);
points = sortrows(points);
%% Initial set of points
plot(points(:,1),points(:,2));
for i = 1: n-1
	len(i) = points(i + 1, 1) - points(i, 1);
end
while(max(len) > 2 * min(len))

caiorss

function [ out_sym, table ] = slice( in_sym, mod_type )
    %SLICE Makes hard decision on input symbols with designated modulation type
    % 
    % Inputs:
    %   in_sym:    input symbols to be sliced 
    %   mod_type:  modulation type, BPSK, QPSK, 16QAM, or 64QAM
    %
    % Outputs:
    %   out_sym:   output symbols
    %   table:     mapping alphabet