Does anyone have any optimized Java or C code for an autocorrelation function. It is my first time needing to do autocorrelation and it seems straight forward enough to be able to write the code myself, but due to the amount of iterations it would be wise to ask for code that already has it's fat trimmed. Thanks in advance. Thomas

# Autocorrelation function, Java or C code

Started by ●June 16, 2006

Reply by ●June 18, 20062006-06-18

#include "stdafx.h" #include <sstream> #include <iostream> #include <fstream> #include <istream> #include <string> #include <vector> #define PI 3.14159265 typedef std::vector<float> float_vec_t; using namespace std; class LPCAnalysis{ public: float_vec_t LPCAnalysis::autoCorrelation(const float_vec_t &x); }; /* Calculate the (un-normalized) autocorrelation for a frame of a signal */ float_vec_t LPCAnalysis::autoCorrelation(const float_vec_t &x) { short order=x.size(); float_vec_t R(order); float sum; int i,j; for (i=0;i<order;i++) { sum=0; for (j=0;j<order-i;j++) { sum+=x[j]*x[j+i]; } R[i]=sum; } return R; } Its in C++ and is very simple but should get you started. Shlomo Kashani. Thomas Magma wrote:> Does anyone have any optimized Java or C code for an autocorrelation > function. It is my first time needing to do autocorrelation and it seems > straight forward enough to be able to write the code myself, but due to the > amount of iterations it would be wise to ask for code that already has it's > fat trimmed. > > Thanks in advance. > Thomas

Reply by ●June 27, 20062006-06-27

For history, here is the Java version of Kalman's below C++ code for the autocorrelation function. Works good! public void autoCorrelation(int size){ float[] R = new R[size]; float sum; for (int i=0;i<size;i++) { sum=0; for (int j=0;j<size-i;j++) { sum+=x[j]*x[j+i]; } R[i]=sum; } } "Kalman" <shlomo_kashani@yahoo.com> wrote in message news:1150638032.157626.100330@f6g2000cwb.googlegroups.com...> #include "stdafx.h" > #include <sstream> > #include <iostream> > #include <fstream> > #include <istream> > #include <string> > #include <vector> > > #define PI 3.14159265 > typedef std::vector<float> float_vec_t; > > using namespace std; > > class LPCAnalysis{ > public: > float_vec_t LPCAnalysis::autoCorrelation(const float_vec_t &x); > > }; > > > /* Calculate the (un-normalized) autocorrelation for a frame of a > signal */ > > float_vec_t LPCAnalysis::autoCorrelation(const float_vec_t &x) > { > short order=x.size(); > > float_vec_t R(order); > float sum; > int i,j; > > for (i=0;i<order;i++) { > sum=0; > for (j=0;j<order-i;j++) { > sum+=x[j]*x[j+i]; > } > R[i]=sum; > } > return R; > } > > Its in C++ and is very simple but should get you started. > > Shlomo Kashani. > > Thomas Magma wrote: >> Does anyone have any optimized Java or C code for an autocorrelation >> function. It is my first time needing to do autocorrelation and it seems >> straight forward enough to be able to write the code myself, but due to >> the >> amount of iterations it would be wise to ask for code that already has >> it's >> fat trimmed. >> >> Thanks in advance. >> Thomas >

Reply by ●June 28, 20062006-06-28

Just for the record, I don't remember if i wrote it or found out sometime ago on the web. Anyway, I am glad you found it helpful. Shlomo Kashani. Thomas Magma wrote:> For history, here is the Java version of Kalman's below C++ code for the > autocorrelation function. Works good! > > public void autoCorrelation(int size){ > float[] R = new R[size]; > float sum; > > for (int i=0;i<size;i++) { > sum=0; > for (int j=0;j<size-i;j++) { > sum+=x[j]*x[j+i]; > } > R[i]=sum; > } > } > > "Kalman" <shlomo_kashani@yahoo.com> wrote in message > news:1150638032.157626.100330@f6g2000cwb.googlegroups.com... > > #include "stdafx.h" > > #include <sstream> > > #include <iostream> > > #include <fstream> > > #include <istream> > > #include <string> > > #include <vector> > > > > #define PI 3.14159265 > > typedef std::vector<float> float_vec_t; > > > > using namespace std; > > > > class LPCAnalysis{ > > public: > > float_vec_t LPCAnalysis::autoCorrelation(const float_vec_t &x); > > > > }; > > > > > > /* Calculate the (un-normalized) autocorrelation for a frame of a > > signal */ > > > > float_vec_t LPCAnalysis::autoCorrelation(const float_vec_t &x) > > { > > short order=x.size(); > > > > float_vec_t R(order); > > float sum; > > int i,j; > > > > for (i=0;i<order;i++) { > > sum=0; > > for (j=0;j<order-i;j++) { > > sum+=x[j]*x[j+i]; > > } > > R[i]=sum; > > } > > return R; > > } > > > > Its in C++ and is very simple but should get you started. > > > > Shlomo Kashani. > > > > Thomas Magma wrote: > >> Does anyone have any optimized Java or C code for an autocorrelation > >> function. It is my first time needing to do autocorrelation and it seems > >> straight forward enough to be able to write the code myself, but due to > >> the > >> amount of iterations it would be wise to ask for code that already has > >> it's > >> fat trimmed. > >> > >> Thanks in advance. > >> Thomas > >

Reply by ●June 28, 20062006-06-28

Thanks Kalman, How about an algorithm for crosscorrelation that I can convert to java (or is that too much to ask)? I imagine that it will be slightly different than the autocorrelation function. In crosscorrelation your regenerated data has to start on one side and slide completely passed your sampled data, but in the autocorrelation function because the two data sets are equal they can start square and can just slip off to one side. It should be twice (-1) as much data output in the cosscorrelation function shouldn't it? Thanks again, Thomas "Kalman" <shlomo_kashani@yahoo.com> wrote in message news:1151508013.558259.191120@x69g2000cwx.googlegroups.com...> Just for the record, I don't remember if i wrote it or found out > sometime ago on the web. > Anyway, I am glad you found it helpful. > > Shlomo Kashani. >

Reply by ●November 17, 20062006-11-17

Hi I'm trying to do pitch tracking (work out if the current spectrum buffer thing is higher or lower frequency than the previous one), using a human voice input from a microphone. I'm using Java written in the processing environment and using the ESS library (ESS has built in fast fourier transforms. check it out at- http://processing.org ). I've little math and programming skill, so would really appreciate if someone could walk me through the next step from Thomas's code (or Thomas if you're listening!). I've modified it so as to not be a class and fit in with what i've done so far. I've got an array 32 floats long which is the spectrum data. I'm assuming that the array x in thomas's code is the equivalent to my spectrum data? i.e. for (int i=0;i<size;i++) { sum=0; for (int j=0;j<size-i;j++) { sum+=x[j]*x[j+i]; } R[i]=sum; } becomes... for (int i=0; i<myFFT.spectrum.length; i++) { sum=0; for (int j=0; j<myFFT.spectrum.length-i; j++) { sum += myFFT.spectrum[j] * myFFT.spectrum[j+i]; } R[i]=sum; } This works fine, and i get an array R with 32 floats which change from about 10e-11 to 10e-5 when i sing into the microphone, but i can't dicern any difference in them when i sing high pitched or low. Now i assume i'm missing another all important step to extract the approximate overall frequency from my voice input. Would anyone out there care to enlighten me?? Please!!! Any help appreciated, Thomas.>For history, here is the Java version of Kalman's below C++ code for the>autocorrelation function. Works good! > >public void autoCorrelation(int size){ > float[] R = new R[size]; > float sum; > > for (int i=0;i<size;i++) { > sum=0; > for (int j=0;j<size-i;j++) { > sum+=x[j]*x[j+i]; > } > R[i]=sum; > } >} > >"Kalman" <shlomo_kashani@yahoo.com> wrote in message >news:1150638032.157626.100330@f6g2000cwb.googlegroups.com... >> #include "stdafx.h" >> #include <sstream> >> #include <iostream> >> #include <fstream> >> #include <istream> >> #include <string> >> #include <vector> >> >> #define PI 3.14159265 >> typedef std::vector<float> float_vec_t; >> >> using namespace std; >> >> class LPCAnalysis{ >> public: >> float_vec_t LPCAnalysis::autoCorrelation(const float_vec_t &x); >> >> }; >> >> >> /* Calculate the (un-normalized) autocorrelation for a frame of a >> signal */ >> >> float_vec_t LPCAnalysis::autoCorrelation(const float_vec_t &x) >> { >> short order=x.size(); >> >> float_vec_t R(order); >> float sum; >> int i,j; >> >> for (i=0;i<order;i++) { >> sum=0; >> for (j=0;j<order-i;j++) { >> sum+=x[j]*x[j+i]; >> } >> R[i]=sum; >> } >> return R; >> } >> >> Its in C++ and is very simple but should get you started. >> >> Shlomo Kashani. >> >> Thomas Magma wrote: >>> Does anyone have any optimized Java or C code for an autocorrelation >>> function. It is my first time needing to do autocorrelation and itseems>>> straight forward enough to be able to write the code myself, but dueto>>> the >>> amount of iterations it would be wise to ask for code that already has>>> it's >>> fat trimmed. >>> >>> Thanks in advance. >>> Thomas >> > > >