Trouble with fmincon - minimizing a vector

Hi, I have a section of raw data and a template vector that I am doing a cosine similarity transform of. I want to maximize the similarity between the two so that I can find the best parameters for the template. I am trying to do this by using fmincon for (1-similarityvalues) to minimize the inverse.

The problem arise when i am trying to input (1-similiarityvalues) as the objective function in fmincon. (1-similiarityvalues) returns a vector of 181x1, but fmincon wants an objective function that returns a scalar value. Is what I'm trying to do even possible? Any tips or advice would be greatly appreciated. Thanks in advance!

A = [];
b = [];
x0 = [0.1, 0.1, 0.1, 0.1];
x = fmincon(@minimize1, x0, A, b);

function min1 = minimize1(x)
    t = x(1);
    alpha = x(2);
    lambda = x(3);
    mu = x(4);
   
    template = alpha.*exp(lambda)/mu.*(lambda.*mu./(2.*pi.*t)).^(1/2).*exp(-lambda./2.*(t./mu+mu./t));

    P005vals = readtable('P005.xlsx', 'Sheet','Sheet1');
    timevals = str2double(P005vals.timevals(1:end));
    bolus1_time = 13221.0;
    bolus1_timeID = find(timevals==bolus1_time);
    deltaT_values = str2double(P005vals.deltaTvals(1:end));
    raw_data = -deltaT_values(bolus1_timeID-60:bolus1_timeID+120);

    simvals1 = correlationfitting(raw_data, template');
    min1 = 1- simvals1;

end

function sim_values = correlationfitting(raw_data, template_data)
    sim_values = zeros(length(raw_data),1);% zeros(length(raw_data),1);
    for i=1:(length(raw_data)-length(template_data))
        raw_chunk = raw_data(i:i+length(template_data)-1);
        sim_value = sum(raw_chunk.*template_data)/(norm(template_data)*(norm(raw_chunk)));
  
        sim_values(i) = sim_value;
    end
end

Answer 1

[Torsten]

The appropriate objective is to minimize

-sum(similiarityvalues.^2)