Hi Everybody,

I am working on pattern matching of EEG signals. Also I am new to this area.
First I segmented the EEG. Each segment is of 200 samples. I have such 64
vectors. I made two templates. One is normal EEG and the other one is abnormal
EEG. All the 64 vectors cluster around these two patterns. The probability of a
vector belonging to a cluster is Gaussian distributed. The probability is given
as

p(x) = (1/(2*pi)^d/2 |C|^1/2)exp(-1/2*(x-m)inv(C)(x-m)

d-dimension

C-covariance matrix of the model

m-mean of the model

x-random variable representing the model

I have attached the program below

I am getting absurd result. That is sum of the probabilities of a vector
belonging to two different clusters is not equal to 1.

I request you if any one of you know this please let me know.

% There are 64 vectors in the data

% Two templates normal and abnormal

%Initialization

normala(1,:);

abnormala(2,:);

pp1=[];

pp2=[];p1=0;

p2=0;

currenta(3,:);

m1=mean(normal);

m2=mean(abnormal);

c1=cov(normal);

c2=cov(abnormal);

p1=1/(((2*pi))*c1^0.5)*exp(-0.5*((current-m1))*(current-m1)'/c1);

p1=1/(((2*pi))*c2^0.5)*exp(-0.5*((current-m2))*(current-m2)'/c2);

Yours Sincerely,

ROSHAN JOY MARTIS

1st Year M. Tech Student

Manipal Institute of Technology

Manipal, South India.

# Regarding probability of Gaussian distribution

Started by ●December 26, 2006