Unit Title Digital Signal Processing
Assignment 2 and Submission Guidelines School School of Information Technology and Engineering Course Name Master of Engineering (Telecommunications) Unit Code ME606 Unit Title Digital Signal Processing Assessment Author Dr. Reza Berangi Assessment Type Assignment 2 (Individual) Assessment Title Review and experimenting some popular signal-processing tasks Unit Learning Outcomes covered in this assessment a. Development and implementation of signal processing algorithms in MATLAB or Scilab b. In-depth design of digital filters c. Understand the design of multirate signal processing and their applications d. Implementation and applications of FFT e. Develop skills in spectral estimation for deterministic and non-deterministic signals Weight 25% Total Marks 100 Word/page limit N/A Release Date Week 7 Due Date Week 11 (Sat. 6 June. 2020, 11:55 pm) Submission Guidelines • Submit on Moodle by the due date along with a completed Assignment Cover Page. • The assignment must be in MS Word format, single line spacing, 11-pt Calibri (Body) font and 2 cm margins on all four sides of your page with appropriate section headings. • Cite references in the text of the report, and listed appropriately at the end in a reference list using IEEE referencing style for School of Business and School of Information Technology and Engineering respectively. Extension For extension of time, submit a Special Consideration Application through the AMS. You must submit this application three working days prior to the due date of the assignment. Further information is available at: http://www.mit.edu.au/about-mit/institute-publications/policies-proceduresand- guidelines/specialconsiderationdeferment Academic Misconduct Academic Misconduct is a serious offence. Depending on the seriousness of the case, penalties can vary from a written warning or zero marks to exclusion from the course or rescinding the degree. Students should make themselves familiar with the full policy and procedure available at: http://www.mit.edu.au/aboutmit/institute-publications/policies-procedures- and-guidelines/PlagiarismAcademic-Misconduct-Policy-Procedure. For further http://www.mit.edu.au/about
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© MIT/SITE | ME606 Digital Signal Processing Assignment 2 Page 2 of 5 information, please refer to the Academic Integrity Section in your Unit Description. ME606 Assessment 2 The objective of this assessment is for each student to demonstrate an understanding of the contents of lecture materials in a signal processing application. Part A In this section you will be familiar with designing and applying digital filters. Use MATLAB “filterDesigner” tool to design variety of filters. Do the following tasks: 1- Create a signal using this code Table 1. Signal generation code f1=5000; % 10KHz f2=10000; % 15KHz f3=15000; % 15KHz fs=48000; % 48KHz sampling frequency N=10000; % length of the signal in samples x=cos(2*pi*f1*(0:N-1)/fs)+cos(2*pi*f2*(0:N-1)/fs)+cos(2*pi*f3*(0:N- 1)/fs); Run the MATLAB command: “filterDesigner” to open MATLAB filter design tool 2. Design a window based FIR filter the following specifications: Table2. Filter design specifications Filter order (length)=111; Fs=48KHz Fc=10KHz Window=hamming ? Show the frequency response you see in the window. ? Export the filter parameters to your workspace and assign the name “b” to that. ? Filter the signal using the command: y=conv(x,b); or y=filter(b,1,x); ? Plot the power spectral density of the signals “x” and “y” using the pwelch command you used in the laboratory experiments. And analyze the effect of filter on each frequency component of the signal x. does the filter perform according to your expectations? 3. Use the Matlab spectrum analyzer tool to see the filter frequency response using the following code. Table 3. Matlab spectrum analyzer program LP_FIR = dsp.FIRFilter(‘Numerator’,b); SA=dsp.SpectrumAnalyzer(‘SampleRate’,Fs,’SpectralAverages’,5); © MIT/SITE | ME606 Digital Signal Processing Assignment 2 Page 3 of 5 tic while toc < 30 x = randn(256,1); y = LP_FIR(x); step(SA,y); end ? Compare the spectrum you see in the spectrum analyzer window and the spectrum you saw in filter design tool. ? Explain what the program in the Table 3 do and what is the role of the random number in thee while loop. 4. Discuss if you under sample the signal x by 2 what parameters should change on your filter design to have the same result. Show that by designing a new filter and applying that to the under-sampled signal. 5. Design a Butterworth IIR filter with the same specifications and order of 6 and measure the magnitude response of the filter at 15 KHs. Design similar FIR filter with Bartlett window and try to reach the same magnitude response, as in section 4, by increasing the filter order (length). What is the length of filter? Which filter is more complex in terms of computational complexity. Discuss the length of filter on the computational complexity of filter. Part B Select only one of the tasks 1 to 4, based on the last 2 digits of your MIT ID modulo 3 +1. For instance, if your ID is MIT152356, 56%3+1= 3 and you must select Task 3. if your ID is MIT173861, 61%3+1=2, you must select Task 2. Write a report asreport as described and submit according to the marking criteria. Task 1: : Review and apply speech signals’ noise reduction with wavelet 1. Give a detailed review of the speech noise reduction using wavelet using the online references and the sample references in the assignment folder. 2. Go to MATWORKS link: https://au.mathworks.com/help/wavelet/ug/wavelet- denoising.html. Read the tutorial, generate a noisy signal and denoise it with the techniques you learned and present and discuss the results by referring to the papers you reviewed in section 1. Task 2: : Review and apply image signals’ noise reduction with wavelet 1. Give a detailed review of the image noise reduction using wavelet using the online references and the sample references in the assignment folder. 2. Go to MATWORKS link: https://au.mathworks.com/help/wavelet/ref/wdenoise2.html Read the tutorial, generate of find a noisy image and denoise it with the techniques you learned and present and discuss the results by referring to the papers you reviewed in section 1. Task 3: Review and apply image segmentation techniques https://au.mathworks.com/help/wavelet/ug/wavelet-denoising.html https://au.mathworks.com/help/wavelet/ug/wavelet-denoising.html https://au.mathworks.com/help/wavelet/ref/wdenoise2.html © MIT/SITE | ME606 Digital Signal Processing Assignment 2 Page 4 of 5 1. Give a detailed review of the image segmentation techniques using the online references and the sample references in the assignment folder. 3. Go to MATWORKS link: https://au.mathworks.com/discovery/image- segmentation.html and read the tutorial and apply one of the segmentation technique on one image using the MATLAB segmentation tool and discuss the results by referring to the papers you reviewed in section 1. Format of the Report: Your report should be typed using a suitable equation editor. Handwritten reports will not be accepted. Marking criteria: Marking criteria is shown in the following table. Sections to be included in the report Detailed Description Marks Repot general section Title, affiliation and abstract Title, Affiliation [your name, Lecturer name, MIT email] Abstract [around 200 words abstract explaining the area, problems, solutions, your contribution] 5 keywords 5 Introduction Introduction (A brief introduction about the Works and the sections of the report) 5 Part A Section 1 and 2 FIR filter design 10 Section 3 Design IIR filter 10 Section 4 Spectrum analyzer 5 Section 5 Multirate signal processing 5 Part B (Task 1 or 2 or 3) Section 1: Literature review Review of the problem domain (critical literature review) 25 Section 2: experiment detail of the implementation methods including Codes, snapshot of the tool menus, graphs and tables with caption and numbered referencing 20 Section 2: Discussion Discussion on the results and qualifying the area of investigation 5 Report General References and formatting Correct in-text referencing and IEEE referencing format. Report style 10 Total 100 https://au.mathworks.com/discovery/image-segmentation.html https://au.mathworks.com/discovery/image-segmentation.html © MIT/SITE | ME606 Digital Signal Processing Assignment 2 Page 5 of 5 Marking Rubric for Exercise Answers: Grade Mark HD 80%+ D 70%- 79% CR 60%- 69% P 50%-59% Fail < 50% Excellent Very Good Good Satisfactory Unsatisfactory Evaluation Logic is clear and easy to follow with strong arguments Consistency logical and convincing Mostly consistent and convincing Adequate cohesion and conviction Argument is confused and disjointed Sophistication and effectivity The presented solution demonstrated an extreme degree of sophistication The presented solution demonstrated a high degree of sophistication The presented solution demonstrated an average degree of sophistication and effectivity to secure The presented solution demonstrated a low degree of sophistication and effectivity to secure The presented solution demonstrated a poor degree of sophistication and effectivity to secure Explanation All elements are present and well integrated. Components present with good cohesion Components present and mostly well integrated Most components present Lacks structure. Reference style Clear styles with excellent source of references. Clear referencing/ style Generally good referencing/style Unclear referencing/style Lacks consistency with many errors Report structure and report presentation Proper writing. Professionally presented Properly written, with some minor deficiencies Mostly good, but some structure or Acceptable presentation Poor structure, careless presentation presentation problems The End Applied Sciences Architecture and Design Biology Business & Finance Chemistry Computer Science Geography Geology Education Engineering English Environmental science Spanish Government History Human Resource Management Information Systems Law Literature Mathematics Nursing Physics Political Science Psychology Reading Science Social Science Home Blog Archive Essay Reviews Contact google+twitterfacebook Copyright © 2019 HomeworkMarket.comHOMEWORKMARKET.COM – YOUR HOMEWORK ANSWERSHomeworkMarket chat0 Home.Homework Answers. Help. Log in / Sign up Unit Title Digital Signal Processing profile naidurupa07 ME606-Assignment-2-Tr1-2020.pdf Home>Computer Science homework help>Unit Title Digital Signal Processing
Assignment 2 and Submission Guidelines School School of Information Technology and Engineering Course Name Master of Engineering (Telecommunications) Unit Code ME606 Unit Title Digital Signal Processing Assessment Author Dr. Reza Berangi Assessment Type Assignment 2 (Individual) Assessment Title Review and experimenting some popular signal-processing tasks Unit Learning Outcomes covered in this assessment a. Development and implementation of signal processing algorithms in MATLAB or Scilab b. In-depth design of digital filters c. Understand the design of multirate signal processing and their applications d. Implementation and applications of FFT e. Develop skills in spectral estimation for deterministic and non-deterministic signals Weight 25% Total Marks 100 Word/page limit N/A Release Date Week 7 Due Date Week 11 (Sat. 6 June. 2020, 11:55 pm) Submission Guidelines • Submit on Moodle by the due date along with a completed Assignment Cover Page. • The assignment must be in MS Word format, single line spacing, 11-pt Calibri (Body) font and 2 cm margins on all four sides of your page with appropriate section headings. • Cite references in the text of the report, and listed appropriately at the end in a reference list using IEEE referencing style for School of Business and School of Information Technology and Engineering respectively. Extension For extension of time, submit a Special Consideration Application through the AMS. You must submit this application three working days prior to the due date of the assignment. Further information is available at: http://www.mit.edu.au/about-mit/institute-publications/policies-proceduresand- guidelines/specialconsiderationdeferment Academic Misconduct Academic Misconduct is a serious offence. Depending on the seriousness of the case, penalties can vary from a written warning or zero marks to exclusion from the course or rescinding the degree. Students should make themselves familiar with the full policy and procedure available at: http://www.mit.edu.au/aboutmit/institute-publications/policies-procedures- and-guidelines/PlagiarismAcademic-Misconduct-Policy-Procedure. For further http://www.mit.edu.au/about
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© MIT/SITE | ME606 Digital Signal Processing Assignment 2 Page 2 of 5 information, please refer to the Academic Integrity Section in your Unit Description. ME606 Assessment 2 The objective of this assessment is for each student to demonstrate an understanding of the contents of lecture materials in a signal processing application. Part A In this section you will be familiar with designing and applying digital filters. Use MATLAB “filterDesigner” tool to design variety of filters. Do the following tasks: 1- Create a signal using this code Table 1. Signal generation code f1=5000; % 10KHz f2=10000; % 15KHz f3=15000; % 15KHz fs=48000; % 48KHz sampling frequency N=10000; % length of the signal in samples x=cos(2*pi*f1*(0:N-1)/fs)+cos(2*pi*f2*(0:N-1)/fs)+cos(2*pi*f3*(0:N- 1)/fs); Run the MATLAB command: “filterDesigner” to open MATLAB filter design tool 2. Design a window based FIR filter the following specifications: Table2. Filter design specifications Filter order (length)=111; Fs=48KHz Fc=10KHz Window=hamming ? Show the frequency response you see in the window. ? Export the filter parameters to your workspace and assign the name “b” to that. ? Filter the signal using the command: y=conv(x,b); or y=filter(b,1,x); ? Plot the power spectral density of the signals “x” and “y” using the pwelch command you used in the laboratory experiments. And analyze the effect of filter on each frequency component of the signal x. does the filter perform according to your expectations? 3. Use the Matlab spectrum analyzer tool to see the filter frequency response using the following code. Table 3. Matlab spectrum analyzer program LP_FIR = dsp.FIRFilter(‘Numerator’,b); SA=dsp.SpectrumAnalyzer(‘SampleRate’,Fs,’SpectralAverages’,5); © MIT/SITE | ME606 Digital Signal Processing Assignment 2 Page 3 of 5 tic while toc < 30 x = randn(256,1); y = LP_FIR(x); step(SA,y); end ? Compare the spectrum you see in the spectrum analyzer window and the spectrum you saw in filter design tool. ? Explain what the program in the Table 3 do and what is the role of the random number in thee while loop. 4. Discuss if you under sample the signal x by 2 what parameters should change on your filter design to have the same result. Show that by designing a new filter and applying that to the under-sampled signal. 5. Design a Butterworth IIR filter with the same specifications and order of 6 and measure the magnitude response of the filter at 15 KHs. Design similar FIR filter with Bartlett window and try to reach the same magnitude response, as in section 4, by increasing the filter order (length). What is the length of filter? Which filter is more complex in terms of computational complexity. Discuss the length of filter on the computational complexity of filter. Part B Select only one of the tasks 1 to 4, based on the last 2 digits of your MIT ID modulo 3 +1. For instance, if your ID is MIT152356, 56%3+1= 3 and you must select Task 3. if your ID is MIT173861, 61%3+1=2, you must select Task 2. Write a report asreport as described and submit according to the marking criteria. Task 1: : Review and apply speech signals’ noise reduction with wavelet 1. Give a detailed review of the speech noise reduction using wavelet using the online references and the sample references in the assignment folder. 2. Go to MATWORKS link: https://au.mathworks.com/help/wavelet/ug/wavelet- denoising.html. Read the tutorial, generate a noisy signal and denoise it with the techniques you learned and present and discuss the results by referring to the papers you reviewed in section 1. Task 2: : Review and apply image signals’ noise reduction with wavelet 1. Give a detailed review of the image noise reduction using wavelet using the online references and the sample references in the assignment folder. 2. Go to MATWORKS link: https://au.mathworks.com/help/wavelet/ref/wdenoise2.html Read the tutorial, generate of find a noisy image and denoise it with the techniques you learned and present and discuss the results by referring to the papers you reviewed in section 1. Task 3: Review and apply image segmentation techniques https://au.mathworks.com/help/wavelet/ug/wavelet-denoising.html https://au.mathworks.com/help/wavelet/ug/wavelet-denoising.html https://au.mathworks.com/help/wavelet/ref/wdenoise2.html © MIT/SITE | ME606 Digital Signal Processing Assignment 2 Page 4 of 5 1. Give a detailed review of the image segmentation techniques using the online references and the sample references in the assignment folder. 3. Go to MATWORKS link: https://au.mathworks.com/discovery/image- segmentation.html and read the tutorial and apply one of the segmentation technique on one image using the MATLAB segmentation tool and discuss the results by referring to the papers you reviewed in section 1. Format of the Report: Your report should be typed using a suitable equation editor. Handwritten reports will not be accepted. Marking criteria: Marking criteria is shown in the following table. Sections to be included in the report Detailed Description Marks Repot general section Title, affiliation and abstract Title, Affiliation [your name, Lecturer name, MIT email] Abstract [around 200 words abstract explaining the area, problems, solutions, your contribution] 5 keywords 5 Introduction Introduction (A brief introduction about the Works and the sections of the report) 5 Part A Section 1 and 2 FIR filter design 10 Section 3 Design IIR filter 10 Section 4 Spectrum analyzer 5 Section 5 Multirate signal processing 5 Part B (Task 1 or 2 or 3) Section 1: Literature review Review of the problem domain (critical literature review) 25 Section 2: experiment detail of the implementation methods including Codes, snapshot of the tool menus, graphs and tables with caption and numbered referencing 20 Section 2: Discussion Discussion on the results and qualifying the area of investigation 5 Report General References and formatting Correct in-text referencing and IEEE referencing format. Report style 10 Total 100 https://au.mathworks.com/discovery/image-segmentation.html https://au.mathworks.com/discovery/image-segmentation.html © MIT/SITE | ME606 Digital Signal Processing Assignment 2 Page 5 of 5 Marking Rubric for Exercise Answers: Grade Mark HD 80%+ D 70%- 79% CR 60%- 69% P 50%-59% Fail < 50% Excellent Very Good Good Satisfactory Unsatisfactory Evaluation Logic is clear and easy to follow with strong arguments Consistency logical and convincing Mostly consistent and convincing Adequate cohesion and conviction Argument is confused and disjointed Sophistication and effectivity The presented solution demonstrated an extreme degree of sophistication The presented solution demonstrated a high degree of sophistication The presented solution demonstrated an average degree of sophistication and effectivity to secure The presented solution demonstrated a low degree of sophistication and effectivity to secure The presented solution demonstrated a poor degree of sophistication and effectivity to secure Explanation All elements are present and well integrated. Components present with good cohesion Components present and mostly well integrated Most components present Lacks structure. Reference style Clear styles with excellent source of references. Clear referencing/ style Generally good referencing/style Unclear referencing/style Lacks consistency with many errors Report structure and report presentation Proper writing. Professionally presented Properly written, with some minor deficiencies Mostly good, but some structure or Acceptable presentation Poor structure, careless presentation presentation problems The End Applied Sciences Architecture and Design Biology Business & Finance Chemistry Computer Science Geography Geology Education Engineering English Environmental science Spanish Government History Human Resource Management Information Systems Law Literature Mathematics Nursing Physics Political Science Psychology Reading Science Social Science Home Blog Archive Essay Reviews Contact google+twitterfacebook Copyright © 2019 HomeworkMarket.com