Part A
1. Define Discrete Time Fourier Transform (DTFT) and its significance in DSP.
2. What are the differences between FIR and IIR filters? Give one example of each.
3. Briefly explain the concept of quantization in digital signal processing.
4. State the Nyquist sampling theorem and explain its importance.
5. What is aliasing? How can it be avoided?
6. Mention some applications of digital signal processing in the field of biomedical engineering.
7. Explain the concept of decimation in the context of multi-rate signal processing.
8. Define the term 'Parseval's theorem' in relation to Fourier analysis.
9. What is a Hilbert Transform? Explain its role in signal processing.
Part B
1. (a) Given the sequence x[n] = {2, 4, 6, 8}, determine its DTFT X(ω) and sketch its magnitude spectrum.
(b) Consider a system with input x[n] and output y[n], described by the difference equation y[n] - 3y[n - 1] + 2y[n - 2] = x[n] . Determine the system's transfer function H(z).
2. (a) Design a 4th order Butterworth low-pass filter with a cut-off frequency of 1 kHz and a sampling frequency of 8 kHz.
(b) Explain the process of analog filter to digital filter transformation using the bilinear transformation method.
3. (a) Discuss the effects of quantization on the frequency response of a DSP system.
(b) Consider a digital system with a 12-bit ADC and a dynamic range of 96 dB. Calculate the quantization noise power in dB.
2021
Part A
1. Explain the concept of linear convolution of two sequences.
2. Define the term 'Z-transform' and mention one of its applications in DSP.
3. What is the difference between Type-I and Type-II Chebyshev filters?
4. Briefly explain the concept of a Goertzel algorithm.
5. Mention the advantage of polyphase implementation of a filter.
6. State the conditions for a system to be linear.
7. Define the term 'cepstrum' and describe its significance in signal processing.
8. What is time reversal? Explain its applications.
9. Mention some applications of DSP in the field of speech processing.
Part B
1. (a) Given two sequences x[n] = {1, 3, 5} and h[n] = {2, -1, 4}, determine their circular convolution using graphical representation.
(b) Consider a digital system with input x[n] and output y[n], described by the difference equation 2y[n] - y[n - 1] + y[n - 2] = x[n] - x[n - 2]. Determine the system's transfer function H(z).
2. (a) Design a 4th order elliptic low-pass filter with pass-band ripple of 1 dB and stop-band attenuation of 40 dB. The pass-band edge is 1 kHz and the stop-band edge is 1.2 kHz.
(b) Explain the concept of cascade and parallel realizations of digital filters.
3. (a) Discuss the effects of finite word length on the stability and performance of a DSP system.
(b) Consider a digital system with a 16-bit ADC and a dynamic range of 120 dB. Calculate the quantization noise level in dB.
2022
Part A
1. Define Sampling theorem and explain its importance in Digital Signal Processing.
2. Distinguish between Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters. Give an example of each.
3. Explain the concept of Decimation in multirate digital signal processing.
4. State and explain Nyquist Criterion for the stability of a discrete-time system.
5. What is the role of quantization in Analog to Digital Conversion?
6. Mention two applications of Digital Signal Processing in the field of image processing.
7. Briefly describe the concept of aliasing in digital signal processing.
8. Define the Discrete Fourier Transform (DFT) and mention one of its properties.
9. What is the significance of the Discrete Wavelet Transform (DWT) in signal analysis and compression?
Part B
1. (a) Given two sequences x[n] = {1, 2, 3, 4} and h[n] = {0, 1, 2, 3}, compute their 4-point circular convolution using the Overlap-Add method.
(b) Consider a digital system with input x[n] and output y[n], described by the difference equation y[n] = 0.5y[n-1] + 2x[n] - 3x[n-1]. Determine the system's transfer function H(z) and draw the corresponding pole-zero plot.
2. (a) Design a lowpass FIR filter of order 10 with a cutoff frequency of 0.2π using the Hamming window method.
(b) Explain the procedure for converting an analog Butterworth filter into a digital filter using the bilinear transformation technique.
3. (a) Derive the expression for the Discrete Fourier Transform (DFT) of a sequence x[n] of length N showing its relation with the DTFT.
(b) Discuss the time and frequency domain aliasing effects in discrete-time signals and suggest methods to minimize them.