function [features1 features2] = simExp(dim, gamma, lambda)
% Generate feature matrix based on exponential distribution
% Inputs:
% 1. dim- number of features
% 2. gamma - constant 
% 3. lambda - constant (if lambda >1, a lot of values = 0)

% P(ith feature = 1) = gamma * exp(-lambda * i)

% Output:
% 1. features1 - feature matrix using class1
% 2. features2 - feature matrix using class2

for i= 1:dim
    classOne(i) = gamma * exp(-lambda * i);
    classTwo(dim-i+1) = classOne(i);    
end
% populating features1 and features2
for i = 1:dim
    tmp = rand();
    if(tmp <=classOne(i))
        features1(i)=1;
    else
        features1(i)=0;
    end
    tmp = rand();
    if(tmp <= classTwo(i))
        features2(i)=1;
    else
        features2(i)=0;
    end
end