Digital Signal Processing (DSP) BEU Question Paper Solution

Digital Signal Processing (DSP) BEU Question Paper Solution:- In this article, I have provided the solution for Digital Signal Processing (DSP) along with its solution based on the BEU question paper. I've strived to make the solutions straightforward so that every student can easily comprehend them.

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This Blog is to provide BEU Solutions to past year's question papers in Digital Signal Processing (DSP) assisting Students in their exam preparation

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BEU PYQ (Previous Years Question) Papers 

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1. Answer any Seven of the following as directed. 2*7=14.

(a) List any two properties of discrete-time systems.

(b) Write the relationship between DFT and Z-transform.

(c) What is the condition on ROC for a system to be causal and stable?

(d) Write the differences between one-sided and two-sided Z-transforms.

(e) How is Chebyshev's approximation different from Butterworth's approximation in terms of the frequency response of an LPF?

(f) If X(k) is the N-point DFT of x(n), then what is the DFT of WN x(n)?

(g) What do you mean by transposed form structure?

(h) Define the term twiddle factor.

(i) What are the salient windowing techniques? features of

(j) Define the term cross-correlation and write its significance.

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2. (a) Determine the solution of the difference equations(n) = 5/6 * y(n – 1) – 1/6 * y(n – 2) + x(n)when the(n) = 2 ^ n * u(n) .forcing function is

(b) A causal system is represented by (n) + 0.25y(n – 1) = x(n) + 0.5x(n – 1)Compute H(z) and find the unit impulse response of the system in analytical form.

3. (a) Explain in detail how a band-limited signal can be reconstructed from its samples in time and frequency domains without any loss of signal information.

(b) Determine the terms sampling theorem, Nyquist rate, Nyquist interval, and aliasing.

4 (a) Determine all possible signals of x(n) associated Z-transforms : (i) X(z) = (ii) X(z) = with the following 1 1-0-5z¹ +0-25z-2 52-1 (1-22-¹)(1-3x-2)

(b) Determine Z-transform and ROC of the finite-duration signal x(n) = (1,0,4,5,7,0,1)

5. (a) State and prove the time reversal property of DFT.

(b) Find the circular convolution of the two sequences x₁(n) = (1,2,3,1} and X2(n) = (4,3,2,2) using the concentric circles method. Verify the results using the DFT IDFT method.

(c) The 4-point DFT x(n) (real sequence) isX(k) = {1, j, 1, – j} . Find the DFT of the following sequences:x 1 (n)=x ((n + 1)) (ii) x 2 (n)=x ((4 – n)) \

6. (a)Realize the following system using direct form-1, direct form-II, cascade form, and parallel form:y(n)=0.75y(n-1)-0.12 overline 5y(n – 2) + 6x(n)- 7x(n – 1) / x * (n – 2)

(b) Realize the FIR filter given byh(n) = (0.5) ^ n * [u(n) – u(n – 4)] using directform-1.

7 (a) Derive the expressions for order and cut-off frequency of a Butterworth filter. 

(b) Determine the system function H(z) of a Chebyshev filter type-1 to meet the following specifications:

• Passband ripple ≤3 dB
• Stopband attenuation 2 20 dB
• Passband edge of 0-3 rad/sample
• Stopband edge of 06 rad/sample
• Use the bilinear transformation method and assume 7 = 1sec.

8. (a) What are the effects of finite register length in the implementation of digital filters?

(b) Explain how the DFT and FFT are helpful in power spectral estimation.

(c) What is the need for multirate signal processing? Explain the process of interpolation and decimation with suitable examples.

9 (a) Obtain the estimate of autocorrelation function and power spectral density for random signals.

(b) Explain the concept of Wiener filtering. Derive weight expression for Wiener filter and also obtain the expression for minimum mean square error.

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