Question

How to Write a function, called multGauss, to compute the sum of multiple Gaussian (normal) profiles in Matlab.

Answer 1

The Gaussian model equation  to compute sum of multiple Gaussian profiles in Matlab is given below.

     

Where

a is the amplitude,

b is the centroid (location),

c is related to the peak width,

n is the number of peaks to fit,

and 1 ≤ n ≤ 8

Now to Write a function, called multGauss in Matlab is as below.

a> function S=sumInt(n) Defining function multGauss as "S"

S=0

for i=1:n

S=S+i

end

end

b> function s = halfsum(A)

[row col] = size(A);

if row ~= col

error('Expecting a square matrix here people...');

end

s = 0;

for ii = 1:row

for jj = ii:col

s = s + A(ii,jj);

end

end

c>  

% Ask user for one integer number.

defaultValue = 45;

titleBar = 'Enter an integer value';

userPrompt = 'Enter the integer';

caUserInput = inputdlg(userPrompt, titleBar, 1, {num2str(defaultValue)});

if isempty(caUserInput),return,end; % Bail out if they clicked Cancel.

% Round to nearest integer in case they entered a floating point number.

integerValue = round(str2double(cell2mat(caUserInput)));

% Check for a valid integer.

if isnan(integerValue)

% They didn't enter a number.

% They clicked Cancel, or entered a character, symbols, or something else not allowed.

integerValue = defaultValue;

message = sprintf('I said it had to be an integer.\nTry replacing the user.\nI will use %d and continue.', integerValue);

uiwait(warndlg(message));

end

d>

n=500;

H1 = normrnd(14,5,n,1); % generate random numbers of normal distribution at mu and sigma

H2 = 24+ normrnd(14,5,n,1); % start from 24

H3 = 48+ normrnd(14,5,n,1);

H4 = 72+ normrnd(14,5,n,1);

H5 = 96+ normrnd(14,5,n,1);

figure

hhh = [H1 H2 H3 H4 H5];

hist(hhh,130)

edges = -20:140;

counts1 = histc(H1, edges);

counts2 = histc(H2, edges)

counts3 = histc(H3, edges);

counts4 = histc(H4, edges);

counts5 = histc(H5, edges);

% Get indexes of first overlap region.

mask = counts1>0 & counts2>0;

% Sum both histograms in that area.

sum1 = sum(counts1(mask)) + sum(counts2(mask))

% Get indexes of second overlap region.

mask = counts2>0 & counts3>0;

% Sum both histograms in that area.

sum2 = sum(counts2(mask)) + sum(counts3(mask))

% Get indexes of third overlap region.

mask = counts3>0 & counts4>0;

% Sum both histograms in that area.

sum3 = sum(counts3(mask)) + sum(counts4(mask))

% Get indexes of fourth overlap region.

mask = counts4>0 & counts5>0;

% Sum both histograms in that area.

sum4 = sum(counts4(mask)) + sum(counts5(mask))