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syms n t;
% Set d to the series, using symsum()
d=1+symsum(sin(n/2*t)*(sin(((n+2)*pi)/(2))*4/(pi^2*n^2)+(-1)^n*2/(n*pi)),n,1,100);
% Prep an x-axis
t=linspace(-10,10,1000);
% Evaluate the values accordingly
data=eval(d);
% And plot it
plot(t,data);

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function [answer] = montecarlo()

N = 100000;
M = 0;

for i = 1:N 
    x = rand-0.5;
    y = rand-0.5; 
    M = M + (sqrt((x^2+y^2)) < 0.5);
end

caiorss

function [m b] = linear_regression(X, Y)
    n = length(Y);
    EX = sum(X);
    EY = sum(Y);
    EX2 = sum(X.*X);
    EXY = sum(X.*Y);
    m = (n*EXY - EX*EY) / (n*EX2 - EX*EX);
    b = (EY - m*EX) / n;
end

caiorss

function [ x,iter ] = gauss_seidel(A,b,itermax,toll,x0)
%ESERCIZIO_2_7_F1 Summary of this function goes here
%   Detailed explanation goes here
% [ x,iter ] = gauss_seidel(A,b,itermax,toll,xo)
%input: 
%     A->matrice sistema lineare ,
%     b-> vettore termine noto,
%     itermax -> numero massimo di iterazioni,
%     toll-> tolleranza richiesta,
%     x0 -> vettore soluzione iniziale

caiorss

function b64 = base64( str )
%BASE64 Encode string (array of chars) into Base64
%   Currently seems to fail for any input > 4 characters. :(
    
    %% Settings
    
    % Valid output codes to choose from.
    base64Chars    = char([65:90, 97:122, 48:57, 43, 47]); % +/ per RFC 2045 et al.
    %base64UrlChars = char([65:90, 97:122, 48:57, 45, 95]); % -_ per RFC 4648 §4
    base64PadChar  = '=';

caiorss

function [f, X, peaks, locs] = plotFFT( t, x, p )
	Fs = 1 / mean(abs(t(2:end) - t(1:end-1)));

	%n = 2^nextpow2(length(x));
	n = length(x);
	X = fft(x-mean(x), n) / length(x);
	f = 0.5*Fs * linspace(0, 1, ceil(0.5*n+1));

	X = X(1:ceil(0.5*n+1));
	mX = abs(X);

caiorss

%% Trial FFT
% http://www.mathworks.co.uk/help/matlab/math/fast-fourier-transform-fft.html

fs =  48000; % Sample Rate
n  =  4096;  % Power of 2 number of samples/ length of FFT

% Get/Generate data
 t = 0:1/fs:10-1/fs;                % 10 sec sample
 x = (1.3)*sin(2*pi*15*t) ...       % 15 Hz component
   + (1.7)*sin(2*pi*40*(t-2)) ...   % 40 Hz component

caiorss

% This scipt loads and plots data from a .mat file
clc
gxFdata = 0;
gyFdata = 0;
gzFdata = 0;


% Loads samples from file
dat = load('GyroSamples.mat');
dat = load('samples.mat');

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names = {}
x = hist(Lifetimes,[50 100 150 200 250 300 350 400])
for i = 1:size(x)
  x(:,i) = x(:,i)./sum(x(:,i))
end
hist(Lifetimes,[50 100 150 200 250 300 350 400])
legend(names)

bins = [50 100 150 200 250 300 350 400];
figure()

caiorss

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