Simple question regarding frequency detection

Bob Cain <arcane@arcanemethods.com> writes:

> Maurice Givens wrote:
> 
> > y = y(:);
> > F = F(:);
> > 
> > 
> 
> Thanks, Maurice.  What do the above two lines do?

If it's matlab, they turn y and F into column vectors.  e.g. if y is 
N x M, then y(:) is NM x 1.

Ciao,

Peter K.

-- 
Peter J. Kootsookos

"I will ignore all ideas for new works [..], the invention of which
 has reached its limits and for whose improvement I see no further
 hope."

- Julius Frontinus, c. AD 84

Peter J. Kootsookos wrote:

> Bob Cain <arcane@arcanemethods.com> writes:
> 
> 
>>Maurice Givens wrote:
>>
>>
>>>y = y(:);
>>>F = F(:);
>>>
>>>
>>
>>Thanks, Maurice.  What do the above two lines do?
> 
> 
> If it's matlab, they turn y and F into column vectors.  e.g. if y is 
> N x M, then y(:) is NM x 1.

Ah, what APL calls the ravel operation.  I've wondered for 
years how to do that in Matlab and was sorta hoping that's 
what it meant when I saw it.


Thanks,

Bob
-- 

"Things should be described as simply as possible, but no 
simpler."

                                              A. Einstein

Atri Mandal <mandala@ics.uci.edu> wrote in message news:<40381039.7751AD38@ics.uci.edu>...
> Hi Maurice,
> Thanks for the code for Goertzel algorithm. It's amazing !!!!
> But I could not make out why this algo should work .. if you have time
> can you please give me a brief explanation as to how this thing works ?
> 
> Thanks,
> Atri.
> 
> 



It's based on the computation of the kth coefficient of the DFT using
a 2nd-order filter.  I suggest a Google search.



Mauricxe Givens

It wasn't clear in the original post if Atri was trying to detect any signal
which contains some energy at 4.5KHz or a signal which is contains only (or
mostly) energy at 4.5 KHz.  A lot of music (and perhaps some speech) will
contain some energy at 4.5Khz, even loud white noise will contain energy at
4.5KHz, if you are trying to detect a signal that is mostly or entirely a
4.5KHz tone and nothing else you will also need to observe the energy in the
rest of the spectra.

The goertzl algorithm is an excellent choice for this problem, but the
detection logic may need to use similar things done in the DTMF decoders in
order to not be fooled by normal signals encountered.  A simple approach is
to compare the energy of the goertzl output to the energy of the entire
signal.  In a signal that is mostly a tone, these will be similar.

-Shawn Steenhagen

"Maurice Givens" <maurice.givens@ieee.org> wrote in message
news:eb93cce8.0402200828.3529a9fd@posting.google.com...
> Atri Mandal <mandala@ics.uci.edu> wrote in message
news:<40359D7A.12B15FED@ics.uci.edu>...
> > Hi,
> > I am writing an application to detect a particular frequency(viz. 4.5
> > Khz) in an input audio signal. I have written the code to capture the
> > sound using a microphone; but I have to properly design a digital filter
> > which will return TRUE as soon as it detects sound of this frequency in
> > the input signal. Also my project demands that I have to detect the
> > signal by looking at a very small number of samples e.g. 44. So I will
> > apply the digital filter on a window of 44 samples of the input signal
> > repeatedly till I get a high response indicating that I have got the
> > reqd. frequency.
> >
> > I know DFT/FFT is an option but are there any better algorithms I can
> > use for my project. Please suggest the best algorithm that will do my
> > work. I am writing the code in C++ so if anyone can point me to existing
> > code on the net that will be really helpful.
> >
> > Thanks,
> > Atri.
>
>
> Here is Matlab code for the Goertzel algm if you just need a
> TRUE/FLASE indication.  Set a threshold, and if y is greater than the
> threshold, then the frequency is detected.
>
> x = input vector
> f = frequency desired
> N = number of samples to test over
> Fs = sample frequency
>
> function y = goert(x,f,N,Fs)
>
> k = fix(0.5 + N*f/Fs);
> w = (2*pi/N)*k;
> coeff = 2 * cos(w);
> Q1 = 0;
> Q2 = 0;
> for j = 1:N
>     Q0 = coeff * Q1 - Q2 + x(j);
>     Q2 = Q1;
>     Q1 = Q0;
> end
> y = sqrt(Q1^2 + Q2^2 - Q1 * Q2 * coeff);
>
>
>
> Here is code to test the alghm.  Plot F aganist y to see the detector
> output as a function of frequency.
>
> fdet is the frequency desired
> N = number of samples to test over
> Fs = sample frequency
>
>
> function [F,y] = testgoert(fdet,N,Fs)
>
> t = 0:1/Fs:((1/Fs)*N - (1/Fs));
> k = 1;
> for f = fix(fdet/2:(fdet/2)/15:fdet*2)
>     x = sin(2*pi*f*t);
>     y(k) = goert(x,fdet,N,Fs);
>     F(k) = f;
>     k = k + 1;
> end
> y = y(:);
> F = F(:);
>
>
> Maurice Givens