% hart_can.m
% Adaline neuron
% Application: Heartbeat Cancellation
% February 20, 2003
% author: G. Dempsey, Bradley University
%

clear
clf

% define y=target, ym= reference

tstep=0.005;                    % 200 Hz sampling
ti=0:tstep:4.995;		% define time base (total)
load hw16			% load unmodified blood P signals

% plot unmodified signals

subplot(211),plot(ti,munmod),grid,title('Mother')
subplot(212),plot(ti,bunmod),grid,title('Baby')

disp('press any key to continue')
pause
% create practical situation

rsig=munmod;			% ref signal (at mother's chest)
tsig=0.4*bunmod+munmod*0.7;	% target signal (at mother's stomach)

figure
subplot(311),plot(ti,tsig),grid,title('Target- stomach')
subplot(312),plot(ti,rsig),grid,title('Reference- chest')
ysub=tsig-rsig;
subplot(313),plot(ti,ysub),grid,title('Subtraction Method')


% define Pattern and Target matrices

T=[tsig]';
ndels=I'm not going to tell;
rdelay=delaysig(rsig',1,ndels)';  % create ?? delayed samples for ANN input

P=[rsig rdelay]';

disp('press any key to continue')
pause
% INITIALIZE NETWORK ARCHITECTURE
%================================

% Set input vector size R, layer sizes S1 & S2, batch size Q.

% left to you

% Initialize weights and biases.

% left to you

% TRAIN THE NETWORK
%==================

% TRAINING PARAMETERS

max_epoch = I'm not going to tell; 
err_goal = I'm not going to tell;
lr = I'm not going to tell;

% PLOT FINAL APPROXIMATION
%=========================
figure
disp('display final results')
subplot(211),plot(ti,bunmod*0.4),grid
title('Desired Output Signal')
%output=? 
subplot(212),plot(ti,output),grid
title('ANN Output')
pause

% SUMMARIZE RESULTS
%==================
% number of epochs
% final sum squared error
% number of delays