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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MATLAB design: Symmetric FIR Filter
% 
% Design pattern covered in this example: 
%  Filter states modeled using DSP System object (dsp.Delay)
%  Filter coefficients passed in as parameters to the design
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%   Copyright 2011-2015 The MathWorks, Inc.

%#codegen
function [y_out, delayed_xout] = mlhdlc_sysobj_ex(x_in, h_in1, h_in2, h_in3, h_in4)
% Symmetric FIR Filter

persistent h1 h2 h3 h4 h5 h6 h7 h8;
if isempty(h1)
    h1 = dsp.Delay;
    h2 = dsp.Delay;
    h3 = dsp.Delay;
    h4 = dsp.Delay;
    h5 = dsp.Delay;
    h6 = dsp.Delay;
    h7 = dsp.Delay;
    h8 = dsp.Delay;
end

h1p = step(h1, x_in);
h2p = step(h2, h1p);
h3p = step(h3, h2p);
h4p = step(h4, h3p);
h5p = step(h5, h4p);
h6p = step(h6, h5p);
h7p = step(h7, h6p);
h8p = step(h8, h7p);

a1 = h1p + h8p;
a2 = h2p + h7p;
a3 = h3p + h6p;
a4 = h4p + h5p;

m1 = h_in1 * a1;
m2 = h_in2 * a2;
m3 = h_in3 * a3;
m4 = h_in4 * a4;

a5 = m1 + m2;
a6 = m3 + m4;

% filtered output
y_out = a5 + a6;
% delayout input signal
delayed_xout = h8p;

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MATLAB test bench for the FIR filter
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%   Copyright 2011-2015 The MathWorks, Inc.

clear mlhdlc_sysobj_ex;
 
x_in = cos(2.*pi.*(0:0.001:2).*(1+(0:0.001:2).*75)).';


h1 = -0.1339;
h2 = -0.0838;
h3 = 0.2026;
h4 = 0.4064;

len = length(x_in);
y_out_sysobj = zeros(1,len);
x_out_sysobj = zeros(1,len);
a = 10;

for ii=1:len
    data = x_in(ii);
    % call to the design 'sfir' that is targeted for hardware
    [y_out_sysobj(ii), x_out_sysobj(ii)] = mlhdlc_sysobj_ex(data, h1, h2, h3, h4);    
end


figure('Name', [mfilename, '_plot']);
subplot(2,1,1); 
plot(1:len,x_in); title('Input signal with noise');
subplot(2,1,2);
plot(1:len,y_out_sysobj); title('Filtered output signal');