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Figure 5. Filtering in the frequency domain.
missing image

Compare the results

The basic plotting format of Figure 5 is the same as Figure 4 .

Compare Figure 5 With Figure 4

The first difference to note between the two figures is that I moved the impulse in the input time series in the topmost plot sixteen samples further tothe right in Dsp038 .

(This has no impact on the final result, which you can verify by modifying the program to move the impulse to a different position and thencompiling and running the modified program.)

Compare the bandwidth of the pass band

The second difference to note is shown in the modified amplitude spectrum in the fourth plot in the two figures. The bandwidth of the pass band issignificantly narrower in Figure 5 than in Figure 4 . Also, the pass band in Figure 4 extends all the way down to zero frequency, while Figure 5 eliminates all energy below a frequency of three thirty-seconds of the sampling frequency.

Waveforms of filtered impulse

Finally, note the waveforms of the two filtered impulses. The overall amplitude of the filtered impulse in Figure 5 is less than in Figure 4 , simply because it contains less total energy. In addition, the filtered impulse in Figure 5 is broader than the filtered impulse in Figure 4 . This is because it has a narrower bandwidth.

(Pulses that are narrow in terms of time duration require a wider bandwidth than pulses that have a longer time duration. The time duration ofthe pulse tends to be inversely related to the required bandwidth for the pulse.)

Run the programs

I encourage you to copy, compile, and run the programs provided in this module. Experiment with them, making changes and observing the results of yourchanges.

Create more complex experiments. For example, use more complex input time series when experimenting with frequency filtering. Apply differentmodifications to the complex spectrum when experimenting with frequency filtering.

Most of all enjoy yourself and learn something in the process.

Summary

This module illustrates and explains forward and inverse Fourier transforms using both DFT and FFT algorithms.

The module also illustrates and explains the implementation of frequency filtering by modifying the complex spectrum in the frequency domain and thentransforming the modified complex spectrum back into the time domain.

Complete program listings

Complete listings of the programs discussed in this module are provided below.

Listings for other programs mentioned in the module, such as Graph03 and Graph06 , are provided in other modules. Those modules are identified in the text of this module.

Listing 14. Dsp035.java.
import java.util.*; class Dsp035 implements GraphIntfc01{final double pi = Math.PI; int len = 256;double[] timeDataIn = new double[len]; double[]realSpect = new double[len];double[] imagSpect = new double[len]; double[]angle = new double[len];//unuseddouble[] magnitude = new double[len]; double[]timeDataOut = new double[len];int zero = 0; public Dsp035(){//constructor//Create the raw data pulses timeDataIn[0]= 0; timeDataIn[1]= 50; timeDataIn[2]= 75; timeDataIn[3]= 80; timeDataIn[4]= 75; timeDataIn[5]= 50; timeDataIn[6]= 25; timeDataIn[7]= 0; timeDataIn[8]= -25; timeDataIn[9]= -50; timeDataIn[10]= -75; timeDataIn[11]= -80; timeDataIn[12]= -60; timeDataIn[13]= -40; timeDataIn[14]= -26; timeDataIn[15]= -17; timeDataIn[16]= -11; timeDataIn[17]= -8; timeDataIn[18]= -5; timeDataIn[19]= -3; timeDataIn[20]= -2; timeDataIn[21]= -1; timeDataIn[240]= 80; timeDataIn[241]= 80; timeDataIn[242]= 80; timeDataIn[243]= 80; timeDataIn[244]= -80; timeDataIn[245]= -80; timeDataIn[246]= -80; timeDataIn[247]= -80; timeDataIn[248]= 80; timeDataIn[249]= 80; timeDataIn[250]= 80; timeDataIn[251]= 80; timeDataIn[252]= -80; timeDataIn[253]= -80; timeDataIn[254]= -80; timeDataIn[255]= -80; //Create raw data sinusoidfor(int x = len/3;x<3*len/4;x++){ timeDataIn[x]= 80.0 * Math.sin( 2*pi*(x)*1.0/20.0);}//end for loop //Compute DFT of the time data and save it in// the output arrays. ForwardRealToComplex01.transform(timeDataIn,realSpect, imagSpect,angle, magnitude,zero, 0.0,1.0); //Compute inverse DFT of spectral data and// save output time data in output array InverseComplexToReal01.inverseTransform(realSpect, imagSpect,timeDataOut); }//end constructor//-------------------------------------------// //The following six methods are required by the// interface named GraphIntfc01. public int getNmbr(){//Return number of curves to plot. Must not // exceed 5.return 5; }//end getNmbr//-------------------------------------------// public double f1(double x){int index = (int)Math.round(x); if(index<0 || index>timeDataIn.length-1){ return 0;}else{ return timeDataIn[index]; }//end else}//end function //-------------------------------------------//public double f2(double x){ int index = (int)Math.round(x);if(index<0 || index>realSpect.length-1){ return 0;}else{ //scale for convenient viewingreturn 5*realSpect[index];}//end else }//end function//-------------------------------------------// public double f3(double x){int index = (int)Math.round(x); if(index<0 || index>imagSpect.length-1){ return 0;}else{ //scale for convenient viewingreturn 5*imagSpect[index];}//end else }//end function//-------------------------------------------// public double f4(double x){int index = (int)Math.round(x); if(index<0 || index>magnitude.length-1){ return 0;}else{ //scale for convenient viewingreturn 5*magnitude[index];}//end else }//end function//-------------------------------------------// public double f5(double x){int index = (int)Math.round(x); if(index<0 || index>timeDataOut.length-1){ return 0;}else{ return timeDataOut[index]; }//end else}//end function }//end sample class Dsp035

Questions & Answers

Ayele, K., 2003. Introductory Economics, 3rd ed., Addis Ababa.
Widad Reply
can you send the book attached ?
Ariel
?
Ariel
What is economics
Widad Reply
the study of how humans make choices under conditions of scarcity
AI-Robot
U(x,y) = (x×y)1/2 find mu of x for y
Desalegn Reply
U(x,y) = (x×y)1/2 find mu of x for y
Desalegn
what is ecnomics
Jan Reply
this is the study of how the society manages it's scarce resources
Belonwu
what is macroeconomic
John Reply
macroeconomic is the branch of economics which studies actions, scale, activities and behaviour of the aggregate economy as a whole.
husaini
etc
husaini
difference between firm and industry
husaini Reply
what's the difference between a firm and an industry
Abdul
firm is the unit which transform inputs to output where as industry contain combination of firms with similar production 😅😅
Abdulraufu
Suppose the demand function that a firm faces shifted from Qd  120 3P to Qd  90  3P and the supply function has shifted from QS  20  2P to QS 10  2P . a) Find the effect of this change on price and quantity. b) Which of the changes in demand and supply is higher?
Toofiq Reply
explain standard reason why economic is a science
innocent Reply
factors influencing supply
Petrus Reply
what is economic.
Milan Reply
scares means__________________ends resources. unlimited
Jan
economics is a science that studies human behaviour as a relationship b/w ends and scares means which have alternative uses
Jan
calculate the profit maximizing for demand and supply
Zarshad Reply
Why qualify 28 supplies
Milan
what are explicit costs
Nomsa Reply
out-of-pocket costs for a firm, for example, payments for wages and salaries, rent, or materials
AI-Robot
concepts of supply in microeconomics
David Reply
economic overview notes
Amahle Reply
identify a demand and a supply curve
Salome Reply
i don't know
Parul
there's a difference
Aryan
Demand curve shows that how supply and others conditions affect on demand of a particular thing and what percent demand increase whith increase of supply of goods
Israr
Hi Sir please how do u calculate Cross elastic demand and income elastic demand?
Abari
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Source:  OpenStax, Digital signal processing - dsp. OpenStax CNX. Jan 06, 2016 Download for free at https://legacy.cnx.org/content/col11642/1.38
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