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Create data arrays

The code in Listing 10 creates the array objects that will be used to store the data until it is retrieved by the methods named f1 through f5 .

Listing 10. Create data arrays.
double[] data = new double[dataLen]; double[]operator = new double[operatorLen]; double[]output = new double[outputLen]; double[]spectrumA = new double[spectrumPts]; double[]spectrumB = new double[spectrumPts];

Beginning of the constructor

Most of the hard work is done by the constructor or by methods called by the constructor.

The code in Listing 11 shows the beginning of the constructor for the class. This code generates and saves the white noise in the array object named data .

Listing 11. Beginning of the constructor.
public Dsp002(){//constructor Random generator = new Random(new Date().getTime()); for(int cnt=0;cnt<data.length; cnt++){//Get data, scale it, remove the // dc offset, and save it.data[cnt] = 100*generator.nextDouble()-50; }//end for loop

The random noise generator seed

Note that by virtue of the way this white noise is being generated, a different seed is passed to the constructor for the Random class each time an object of the Dsp002 class is instantiated. Thus, each new object presents different random noise.

(In some cases, this may not be desirable and it may be preferable to use the same seed each time an object is instantiated.)

Create the convolution operator

The code in Listing 12 creates the 33-point convolution operator, as a segment of a cosine wave, and saves it in the designated array.

Listing 12. Create the convolution operator.
for(int cnt = 0; cnt<operatorLen; cnt++){operator[cnt] = Math.cos(cnt*2*Math.PI/4); }//end for loop

Note that the constant value of 4 in the denominator of the argument to the cos method specifies the frequency of the cosine wave relative to the sampling frequency. (In this case, the frequency of the cosine wave is one-fourth the sampling frequency.)

Apply the convolution operator

The code in Listing 13 calls a static method named convolve in a class named Convolve01 to apply the convolution operator to the white noise and save the filtered result in the appropriate array. I will briefly discuss this methodlater.

Listing 13. Apply the convolution operator.
Convolve01.convolve(data,dataLen, operator,operatorLen,output);

Compute spectrum of each of two traces

The code in Listing 14 calls a static method named dft of a class named Dft01 twice in succession to compute the spectra for the white noise and the filterednoise, and to save those spectra in the appropriate arrays.

Listing 14. Compute spectrum of each of two traces.
Dft01.dft(data,spectrumPts, spectrumA);Dft01.dft(output,spectrumPts, spectrumB);}//end constructor

All results have been computed and saved

That is the end of the constructor. At this point, all the results have been computed and saved in the appropriate arrays for later retrieval by the methodsnamed f1 through f5 .

Questions & Answers

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Bob Reply
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are you nano engineer ?
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what is the actual application of fullerenes nowadays?
That is a great question Damian. best way to answer that question is to Google it. there are hundreds of applications for buck minister fullerenes, from medical to aerospace. you can also find plenty of research papers that will give you great detail on the potential applications of fullerenes.
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carbon nanotubes has various application in fuel cells membrane, current research on cancer drug,and in electronics MEMS and NEMS etc
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s. Reply
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Do you know which machine is used to that process?
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of graphene you mean?
or in general
in general
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