+1 862 207 3288 Instructions to Student:
Each question carries 5 Marks.
Each student will be given an assignment question for 20 Marks.
Assignment answers must be computer typed. Please do not write question statement. Just mention the question number.
Font – Times New Roman
Font – Style – Regular
Font – Size – 12
Title Page must have Assignment Name, Module name, your name, ID, section and the name of the faculty.
“Handel.mat” &”Lena image” will be provided.
Soft copy of the assignment is to be submitted online inMoodle through turnitin.
Each student has to do the assignment individually.
Explain your notations and stepsexplicitly and clearly.
You can refer books in Library or use internet resource. But you should not cut and paste material from internet nor provide photocopied material from books. The assignment answers should be in your own words after understanding the matter from the above resources.
Rules & Regulations
If any coursework assessment is found to be copied from other candidates using unacceptable means, then it shall be cancelled and the total marks awarded will be zero. No chance of resubmission or appeal will be given*.
Your source of information should be mentioned in the reference page clearly. (For example: If it’s from book, you have to mention the full details of the book with title, author name, edition and publisher’s name. If it is from the internet you have to mention the correct URL). Otherwise the assignment will be considered as plagiarized*.
The students may be asked to appear for a viva voce to validate the assignment solutions submitted. The viva voce does not carry any marks.
For late submission, 5% of the awarded marks will be deducted for each working day.
For plagiarism, please refer to student guide and clarification uploaded on Moodle.
Refer MIG for feedback dates on assignment.
No assignment will be accepted after one week from the date of submission*.
*Refer to the MIG for MEC policy on academic integrity and late submission.
Genrate and plot the samples using stem function for the following signals: (matlap) (3 Marks)
x_1 [n]=5δ[n+1]+n^2 (u[n+5]-u[n-4] )+10(0.5)^n (u[n-4]-u[n-8] )
x_2 [n]=(0.8)^n cos(0.2πn+π/4), 0≤n≤20.
x_3 [n]=∑_(m=0)^4▒(m+1){δ[n-m]-δ[n-2m]} , 0≤n≤20
What is Imaging and Aliasing? How their Spectrum differ from each other? What is the need forAnti Aliasing filter prior to down sampling? (2 Marks)
Note: Support your answers with appropriate explanation and figures. Provide references also.
The difference equation describing the input−output relationship of a discrete LTI system is
y[n]-0.5y[n-1]+0.125y[n-2]=x[n]+x[n-1]
Compute the following:
Transfer function of the system, H(z).
Impulse response (h[n] )of the discrete time. Also implement in matlab.
Output response of the system when the input is unit step u[n]. Also compute the unit step output using matlab Simulink. (2 Marks)
Let the signal to be filtered be the first 100 samples from MATLAB’s “train” signal. To this signal add some Gaussian noise to be generated by randn, multiply it by 0.1, and add it to the 100 samples of the train signal. Design three discrete filters, each of order 20, and a half frequency (for Butterworth butter) and passband frequency (for the Chebyshev filters) of ω_n=0.5. For the design with cheby1 let the maximum passband attenuation be 0.01 dB, and for the design with cheby2 let the minimum stopband attenuation be 60 dB. Obtain the three filters and use them to filter the noisy “train” signal.
Use MATLAB plot the following for each of the three filters:
Using fft function compute the DFT of the original signal, the noisy signal and the noise and plot its magnitude. Is the cut-iff frequency of thefilters adequate to get rid of the noise? Explain. (1.5 Marks)
Compute and plot the magnitude and poles & zeros for each of the three filters. Comment on the differences in the magnitude responses. (1.5 Marks)
Use the filter function to obtain the output of each of the filters. Also plot the original noiseless signal and filtered signal. Compare them. (2 Marks)
In this problem use Lena image to compute the output.
Load the Lena image in MATLAB and display using imshow function. (1 Mark)
Consider the 1D (single dimensional) impulse response h[n]=1/5 {█(1,1,1,1,1@ ↑)}. Using it perform 1D convolution along the each row of the Lena image and display the resulting blurred image. Comment on the result. (2 Marks)
Using the image obtained in part (b) perform 1D convolution along the each column of the Lena image and display the resulting blurred image. Compare this image with the image in part (b) and comment on the results. (2 Marks)
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