R=0.01;
Q=0.00001;
updatedState=-0.37727;%initial value stated in data.m
updatedCovariance=R;%initial covariance is the measured covariance, R
Vmeasured=zeros(1,50);%initialized 50 zeroes to Vmeasured
Vkalman=zeros(1,50);

for i=1:1:50
    if i~=1
    predictedState=updatedState;%A=1 and B=0, there is no input
    predictedCovariance=updatedCovariance + Q;%A=1
    innovation=voltage(i) - predictedState;%H=1
    innovationCovariance=predictedCovariance + R;
    kalmanGain=predictedCovariance * innovationCovariance^-1;
    updatedState=predictedState + kalmanGain * innovation;
    updatedCovariance=(1-kalmanGain) * predictedCovariance;%I matrix=1 here, H=1
    Vkalman(i)=updatedState;
    end
end

for i=1:1:50
    Vmeasured(i)=-0.37727;
end
...
...