//Practical 1 (Generation of Discrete Signals)

//Unit Impluse Signal (1,for n=0 or 0,otherwise)
y1 = zeros(1,21);
y1(1,11) = 1;
subplot(3,2,1);
plot2d3(y1);
title("Unit Impluse Signal");

//Unit Step Signal (1, for n>=0 or 0, for n<0)
y2 = zeros(1,21);
y2(1,11:21) = 1;
subplot(3,2,2);
plot2d3(y2);
title("Unit Step Signal");

//Unit Ramp Signal (n,for n>=0 or 0,for n<0)
y3=0:10;
subplot(3,2,3);
plot2d3(y3);
title("Unit Ramp Signal");

//Exponential Signal

//Increasing
t = -2:0.1:2;
x = exp(t);
subplot(3,2,4);
plot(t,x);
title("Exponential Increasing");

//Decreasing
t = -2:0.1:2;
x = exp(-t);
subplot(3,2,5);
plot(t,x);
title("Exponential Decreasing");


//Practical 2 (Linear Convolution of two sequence)

//Linear Convolution of two sequence
x = [1,2,3,4];
h = [1,1,1];
l1 = length (x);
l2 = length (h);
L = l1+l2-1;
x = [x,zeros(1,L-l1)];
h = [h,zeros(1,L-l2)];
y = zeros(1,L);
for n=1:L;
    for k=1:n
        y(n) = y(n)+x(k)*h(n-k+1);
    end
end
disp(y);
//Plotting
ny = 0:L-1;
subplot(3,1,1);
plot2d3(ny,x);
title("For x");
subplot(3,1,2);
plot2d3(ny,h);
title("For h");
subplot(3,1,3);
plot2d3(ny,y);
title("For y");

//Practical 3 (Circular Convolution of two Sequence)

//Circular Convolution of two sequence
xn = [1,2,3,4];
xn = mtlb_fliplr(xn);
hn = [2,1,2,1];
x1 = xn;
h1 = hn;
for i=1:length(xn);
    x1=[x1($)x1(1:$-1)];
    h1 = hn;
    ycc(i) = sum(x1.*h1);
    disp(ycc(i));
end

//Practical 4 (Perform Circular Convolution using DFT and IDFT)

x1 = input("Enter Input Sequence for x1(n) : ");
x2 = input("Enter Input Sequence for x2(n) : ");
l1 = length(x1);
l2 = length(x2);
if l1 == l2 then
    a=fft(x1,-1);
    b=fft(x2,-1);
    x3 = a.*b;
    disp(x3);
    x4=ifft(x3);
    disp(x4);
elseif l1<l2
    x1 = [x1,zeros(1,l2-l1)];
    a=fft(x1,-1);
    b=fft(x2,-1);
    x3 = a.*b;
    disp(x3);
    x4=ifft(x3);
    disp(x4);
else
    x2 = [x2,zeros(1,l1-l2)];
    a=fft(x1,-1);
    b=fft(x2,-1);
    x3 = a.*b;
    disp(x3);
    x4=ifft(x3);
    disp(x4);
end


//Practical 5 ( Perform Linear convolution using circular convolution method)

//Linear Convolution method using circular convolution method
xn = [1,2,3,1,0,0];
hn = [1,1,1,0,0,0];
xn = mtlb_fliplr(xn);
x1 = xn;
h1 = hn;
for i=1:length(xn);
    x1 = [x1($)x1(1:$-1)];
    h1 = hn;
    ycc(i) = sum(x1.*h1);
    disp(ycc(i));
end

//Practical 6 (Perform FFT and IFFT of a discrete sequence)

//DSP Practical 6 (Butterfly Method)
clear;
x = [1,1,0,0,1,1,0,0];
n = [0,4,2,6,1,5,3,7]+1;
for i=1:8
    s=n(i);
    xn(i)=x(s);
end

//Stages
O = xn;
N = length(x);
S = log2(N);
cnt=1;

//Stage 1
for n=1:2:N-1
    w8_0=exp(-1*%i*2*%pi*0/N);
    f(cnt)=O(n)+O(n+1)*w8_0;
    f(cnt+1)=O(n)-O(n+1)*w8_0;
    cnt=cnt+2;
end
disp(f)

//Stage 2
cnt=1;
for n=1:4:N-1
    w8_0=exp(-1*%i*2*%pi*0/N);
    w8_2=exp(-1*%i*2*%pi*2/N);
    G(cnt)=f(n)+f(n+2)*w8_0;
    G(cnt+2)=f(n)-f(n+2)*w8_0;
    G(cnt+1)=f(n+1)+f(n+3)*w8_2;
    G(cnt+3)=f(n+1)-f(n+3)*w8_2;
    cnt=cnt+4;
end
disp(G)

//Stage 3
cnt=1;
for n = 1:N/2
    w8 = exp(-1*%i*2*%pi/N);
    X(cnt) = G(n)+G(n+4)*w8^(n-1);
    X(cnt+4) = G(n)-G(n+4)*w8^(n-1);
    cnt = cnt+1;
end
disp(X)


//Practical 7 (To design a FIR filter using window technique)

//DSP Practical 7 (Rectangle Window)
clc;clear;
tmin = 0;tmax = 1;
t = linspace(tmin,tmax,256);
[fir_time,fir_freq,fr] = wfir("lp",133,[.2,0],"re",[0,0]);
subplot(2,2,1);
title('h(n)');
plot(fir_time);

subplot(2,2,2);
title('H(W)');
plot(fir_freq);

X = sin(2*%pi*t*64)+sin(2*%pi*t*128)+sin(2*%pi*t*256);
subplot(2,2,3);
Y = fft(X);
title('Signal IFFT');

plot(abs(Y));
subplot(2,2,4);

YF = abs(Y).*fir_freq;
title('FIR Filtered Signal');
plot(abs(YF));