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Listing 13. Dsp033a.java.
/* File Dsp033a.java Copyright 2004, R.G.BaldwinRevised 5/17/2004 Displays sinusoidal pulses identical to thoseprocessed by Dsp033. Creates and displays five separate time series,each 400 samples in length. Each time series contains a pulse and the pulsesare different lengths. Each pulse consists of the sum of two sinusoidsat closely spaced frequencies. The frequencies of the two sinusoids are equidistant from 0.0625times the sampling frequency. The total separation between the frequencies of the twosinusoids is the reciprocal of the length of the pulse.All frequency values are specified as type double as a fraction of the sampling frequency.The lengths of the pulses are: 25 samples50 samples 100 samples200 samples 400 samplesTested using J2SEE 1.4.2 under WinXP. ************************************************/import java.util.*; class Dsp033a implements GraphIntfc01{final double pi = Math.PI; int len = 400;//data lengthint numberPulses = 5; //Frequencies of the sinusoidsdouble freq1a = 0.0625 - 8.0/len; double freq2a = 0.0625 + 8.0/len;double freq1b = 0.0625 - 4.0/len; double freq2b = 0.0625 + 4.0/len;double freq1c = 0.0625 - 2.0/len; double freq2c = 0.0625 + 2.0/len;double freq1d = 0.0625 - 1.0/len; double freq2d = 0.0625 + 1.0/len;double freq1e = 0.0625 - 0.5/len; double freq2e = 0.0625 + 0.5/len;//Amplitude of the sinusoids double amp = 160;//Following arrays will contain sinusoidal data double[]data1 = new double[len];double[] data2 = new double[len]; double[]data3 = new double[len];double[] data4 = new double[len]; double[]data5 = new double[len];public Dsp033a(){//constructor //Create the raw datafor(int x = 0;x<len/16;x++){ data1[x]= amp*Math.cos(2*pi*x*freq1a) + amp*Math.cos(2*pi*x*freq2a);}//end for loop for(int x = 0;x<len/8;x++){ data2[x]= amp*Math.cos(2*pi*x*freq1b) + amp*Math.cos(2*pi*x*freq2b);}//end for loop for(int x = 0;x<len/4;x++){ data3[x]= amp*Math.cos(2*pi*x*freq1c) + amp*Math.cos(2*pi*x*freq2c);}//end for loop for(int x = 0;x<len/2;x++){ data4[x]= amp*Math.cos(2*pi*x*freq1d) + amp*Math.cos(2*pi*x*freq2d);}//end for loop for(int x = 0;x<len;x++){ data5[x]= amp*Math.cos(2*pi*x*freq1e) + amp*Math.cos(2*pi*x*freq2e);}//end for loop }//end constructor//-------------------------------------------// //The following six methods are required by the// interface named GraphIntfc01. public int getNmbr(){//Return number of functions to process. // Must not exceed 5.return 5; }//end getNmbr//-------------------------------------------// public double f1(double x){int index = (int)Math.round(x); if(index<0 || index>data1.length-1){ return 0;}else{ //Scale the amplitude of the pulses to make// them compatible with the default // plotting amplitude of 100.0.return data1[index]*40.0/amp;}//end else }//end function//-------------------------------------------// public double f2(double x){int index = (int)Math.round(x); if(index<0 || index>data2.length-1){ return 0;}else{ return data2[index]*40.0/amp; }//end else}//end function //-------------------------------------------//public double f3(double x){ int index = (int)Math.round(x);if(index<0 || index>data3.length-1){ return 0;}else{ return data3[index]*40.0/amp; }//end else}//end function //-------------------------------------------// public double f4(double x){int index = (int)Math.round(x); if(index<0 || index>data4.length-1){ return 0;}else{ return data4[index]*40.0/amp; }//end else}//end function //-------------------------------------------//public double f5(double x){ int index = (int)Math.round(x);if(index<0 || index>data5.length-1){ return 0;}else{ return data5[index]*40.0/amp; }//end else}//end function }//end sample class Dsp033a
Listing 14. File Dsp033.java.
/* File Dsp033.java Copyright 2004, R.G.BaldwinRevised 5/17/2004 Same as Dsp032 except that the separation betweenthe frequencies of the two sinusoids is the reciprocal of the length of the pulse.Performs spectral analysis on five separate time series, each 400 samples in length.Each time series contains a pulse and the pulses are different lengths.Each pulse consists of the sum of two sinusoids at closely spaced frequencies. The frequenciesof the two sinusoids are equidistant from 0.0625 times the sampling frequency. The totalseparation between the frequencies of the two sinusoids is the reciprocal of the length of thepulse. All frequency values are specified as typedouble as a fraction of the sampling frequency. The lengths of the pulses are:25 samples 50 samples100 samples 200 samples400 samples The spectral analysis computes the spectra at400 equally spaced points between zero and the folding frequency (one-half the samplingfrequency). The results of the spectral analysis aremultiplied by the reciprocal of the lengths of the individual pulses to normalize the fiveplots. Otherwise, the results for the short pulses would be too small to see on the plots.Tested using J2SEE 1.4.2 under WinXP. ************************************************/import java.util.*; class Dsp033 implements GraphIntfc01{final double pi = Math.PI; int len = 400;//data length//Sample that represents zero time. int zeroTime = 0;//Low and high frequency limits for the // spectral analysis.double lowF = 0.0; double highF = 0.5;int numberSpectra = 5; //Frequencies of the sinusoidsdouble freq1a = 0.0625 - 8.0/len; double freq2a = 0.0625 + 8.0/len;double freq1b = 0.0625 - 4.0/len; double freq2b = 0.0625 + 4.0/len;double freq1c = 0.0625 - 2.0/len; double freq2c = 0.0625 + 2.0/len;double freq1d = 0.0625 - 1.0/len; double freq2d = 0.0625 + 1.0/len;double freq1e = 0.0625 - 0.5/len; double freq2e = 0.0625 + 0.5/len;//Amplitude of the sinusoids double amp = 160;//Following arrays will contain data that is // input to the spectral analysis process.double[] data1 = new double[len]; double[]data2 = new double[len];double[] data3 = new double[len]; double[]data4 = new double[len];double[] data5 = new double[len]; //Following arrays receive information back// from the spectral analysis that is not used // in this program.double[] real;double[] imag;double[] angle;//Following arrays receive the magnitude // spectral information back from the spectral// analysis process. double[]mag1; double[]mag2; double[]mag3; double[]mag4; double[]mag5; public Dsp033(){//constructor//Create the raw data for(int x = 0;x<len/16;x++){ data1[x]= amp*Math.cos(2*pi*x*freq1a) + amp*Math.cos(2*pi*x*freq2a);}//end for loop for(int x = 0;x<len/8;x++){ data2[x]= amp*Math.cos(2*pi*x*freq1b) + amp*Math.cos(2*pi*x*freq2b);}//end for loop for(int x = 0;x<len/4;x++){ data3[x]= amp*Math.cos(2*pi*x*freq1c) + amp*Math.cos(2*pi*x*freq2c);}//end for loop for(int x = 0;x<len/2;x++){ data4[x]= amp*Math.cos(2*pi*x*freq1d) + amp*Math.cos(2*pi*x*freq2d);}//end for loop for(int x = 0;x<len;x++){ data5[x]= amp*Math.cos(2*pi*x*freq1e) + amp*Math.cos(2*pi*x*freq2e);}//end for loop //Compute magnitude spectra of the raw data// and save it in output arrays. Note that // the real, imag, and angle arrays are not// used later, so they are discarded each // time a new spectral analysis is performed.mag1 = new double[len];real = new double[len];imag = new double[len];angle = new double[len];ForwardRealToComplex01.transform(data1,real, imag,angle,mag1,zeroTime,lowF,highF);mag2 = new double[len];real = new double[len];imag = new double[len];angle = new double[len];ForwardRealToComplex01.transform(data2,real, imag,angle,mag2,zeroTime,lowF,highF);mag3 = new double[len];real = new double[len];imag = new double[len];angle = new double[len];ForwardRealToComplex01.transform(data3,real, imag,angle,mag3,zeroTime,lowF,highF);mag4 = new double[len];real = new double[len];imag = new double[len];angle = new double[len];ForwardRealToComplex01.transform(data4,real, imag,angle,mag4,zeroTime,lowF,highF);mag5 = new double[len];real = new double[len];imag = new double[len];angle = new double[len];ForwardRealToComplex01.transform(data5,real, imag,angle,mag5,zeroTime,lowF,highF);}//end constructor //-------------------------------------------////The following six methods are required by the // interface named GraphIntfc01.public int getNmbr(){ //Return number of functions to process.// Must not exceed 5. return 5;}//end getNmbr //-------------------------------------------//public double f1(double x){ int index = (int)Math.round(x);if(index<0 || index>mag1.length-1){ return 0;}else{ //Scale the magnitude data by the// reciprocal of the length of the sinusoid // to normalize the five plots to the same// peak value. return mag1[index]*16.0; }//end else}//end function //-------------------------------------------//public double f2(double x){ int index = (int)Math.round(x);if(index<0 || index>mag2.length-1){ return 0;}else{ return mag2[index]*8.0; }//end else}//end function //-------------------------------------------//public double f3(double x){ int index = (int)Math.round(x);if(index<0 || index>mag3.length-1){ return 0;}else{ return mag3[index]*4.0; }//end else}//end function //-------------------------------------------//public double f4(double x){ int index = (int)Math.round(x);if(index<0 || index>mag4.length-1){ return 0;}else{ return mag4[index]*2.0; }//end else}//end function //-------------------------------------------//public double f5(double x){ int index = (int)Math.round(x);if(index<0 || index>mag5.length-1){ return 0;}else{ return mag5[index]*1.0; }//end else}//end function }//end sample class Dsp033

Miscellaneous

This section contains a variety of miscellaneous information.

Housekeeping material
  • Module name: Java1483-Spectrum Analysis using Java, Frequency Resolution versus Data Length
  • File: Java1483.htm
  • Published: 08/10/04

Baldwin provides the code and explains the requirements for using spectral analysis to resolve spectral peaks for pulses containing closely spaced truncated sinusoids.

Disclaimers:

Financial : Although the Connexions site makes it possible for you to download a PDF file for thismodule at no charge, and also makes it possible for you to purchase a pre-printed version of the PDF file, you should beaware that some of the HTML elements in this module may not translate well into PDF.

I also want you to know that, I receive no financial compensation from the Connexions website even if you purchase the PDF version of the module.

In the past, unknown individuals have copied my modules from cnx.org, converted them to Kindle books, and placed them for sale on Amazon.com showing me as the author. Ineither receive compensation for those sales nor do I know who does receive compensation. If you purchase such a book, please beaware that it is a copy of a module that is freely available on cnx.org and that it was made and published withoutmy prior knowledge.

Affiliation : I am a professor of Computer Information Technology at Austin Community College in Austin, TX.

-end-

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