Kindly verify my code of DTMF decoding step
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I want to decode DTMF tones by using FIR Filter. The filters that are required to be used in filter bank are cnstructed by Sinusoidal impulse response of the form h[n]= (2/L)cos(2*pi*fb*n/fs) where 0<n<L
L is filter length fb defines the freq location of passband e.g we can pick 697Hz
the book says to generate bandpass filter for 770 Hz component with L=50 and fs=12000. This has to be done by creating a vector of filter co-efficients ,h770 which are determined by evaluatiing above stated equation. plot the filter coefficients using stem().
I have done it in this way. Is it ok
h=[];
L=50;
fs=12000;
fb=770;
for n=1:L
h(n)=(2/L)*cos(2*pi*fb*n/fs);
end
stem(h)
1 Comment
Jan
on 9 Oct 2011
Please check the results with some test data.
Accepted Answer
More Answers (10)
moonman
on 9 Oct 2011
0 votes
Walter Roberson
on 9 Oct 2011
0 votes
The description says 0 < n < L but you have n going from 1 to L which is one step too far (n == L)
3 Comments
Walter Roberson
on 9 Oct 2011
Notice the strict inequality: 0 < n < L . That means that n cannot be 0 and cannot be L, so there is no need to use "for n=0:L" (not unless the instructions are wrong.)
If the instructions had said 0 <= n <= L, then you would code as
for n=0:L
h(n+1)=(2/L)*cos(2*pi*fb*n/fs);
end
moonman
on 9 Oct 2011
Walter Roberson
on 9 Oct 2011
for n=0:L-1
h(n+1)=(2/L)*cos(2*pi*fb*n/fs);
end
moonman
on 9 Oct 2011
moonman
on 9 Oct 2011
0 votes
1 Comment
Wayne King
on 9 Oct 2011
Yes, you can confirm by looking at the frequency response
fvtool(h,1,'Fs',fs);
moonman
on 9 Oct 2011
1 Comment
Wayne King
on 9 Oct 2011
The big difference is that you have not plotted yours in dB
plot(ff,abs(H));
% if you plot
plot(ff,20*log10(abs(H)));
You'll see. I think it is much more common to plot these in dB.
Wayne King
on 9 Oct 2011
fvtool() is doing that under the hood and much more, I question why your book constructs a frequency axis in angular frequencies, when in this application Hertz makes much more sense:
[H,F] = freqz(h,1,[],fs);
plot(F./1000,20*log10(abs(H)));
grid on;
xlabel('kHz'); ylabel('Magnitude-squared (dB)');
Again, I would recommend you avoid a for loop to calculate your FIR filter coefficients and just use the vector approach I showed above.
moonman
on 9 Oct 2011
Wayne King
on 9 Oct 2011
[H,F] = freqz(h,1,[],fs);
plot(F,20*log10(abs(H)));
grid on;
xlabel('Hz'); ylabel('Magnitude-squared (dB)');
set(gca,'xtick',[697,770,852,941,1209,1336,1477]);
set(gca,'xlim',[500 2000]);
Note that you really need to limit your x-axis in order to make the labels reasonable. If you use the whole frequency axis from 0 to the Nyquist, they bunch up.
moonman
on 9 Oct 2011
0 votes
moonman
on 17 Oct 2011
5 Comments
moonman
on 17 Oct 2011
Wayne King
on 17 Oct 2011
It is often desirable to obtain power estimates, which is the magnitude squared.
moonman
on 17 Oct 2011
Jan
on 17 Sep 2013
@praveen: This request is such unfriendly, that it is funny, that you hope to be successful. It is definitely your turn to pick from these many pieces of code a program, that is working for you. Trying to push us to do your work quickly is really the wrong approach.
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