Digital Signal Processing

The output of an LTI system can be determined using

1. Sampling
2. Convolution
3. Quantization
4. Modulation

Which of the following is an advantage of DSP over analog systems?

1. More noise
2. Less flexibility
3. Better accuracy and reliability
4. Difficult storage

A system is said to be LTI if it is

1. Linear and Time Invariant
2. Linear and Time Variant
3. Logical and Time Invariant
4. Linear and Tuned

Convolution is used to determine

1. Frequency response
2. System output
3. Sampling frequency
4. Fourier coefficients

The DTFT of a discrete-time signal is

1. Always periodic
2. Non-periodic
3. Finite
4. Real only

Aliasing occurs when the sampling frequency is

1. Greater than Nyquist rate
2. Equal to Nyquist rate
3. Less than Nyquist rate
4. Double the signal frequency

FFT is mainly used to

1. Increase noise
2. Reduce computational complexity of DFT
3. Amplify signals
4. Sample analog signals

Correlation is used to measure

1. Power consumption
2. Similarity between signals
3. Frequency distortion
4. Sampling error

The DFT converts a signal from

1. Time domain to frequency domain
2. Frequency domain to time domain
3. Analog to digital
4. Continuous to discrete amplitude

Nyquist sampling theorem states that sampling frequency should be

1. Equal to signal frequency
2. Twice the maximum frequency
3. Half the maximum frequency
4. Four times the signal frequency

Explain the basic elements of a Digital Signal Processing system with block diagram.

Discuss the advantages of DSP over analog signal processing systems.

Classify signals into continuous-time and discrete-time signals with examples.

Define Linear Time Invariant (LTI) systems and explain their properties.

Explain convolution sum and determine the response of an LTI system. Use:
y[n] = x[n] * h[n] = Σ_k=−∞^∞ x[k]h[n − k]

Describe discrete-time systems using difference equations.

Define Discrete Time Fourier Transform.

Explain the properties of DTFT with examples. Use:
X(e^jω) = Σ_n=−∞^∞ x[n] e^−jωn

Explain frequency domain representation of LTI systems.

Derive the mathematical expression of DFT. Use:
X[k] = Σ_n=0^N−1 x[n] e^{−j(2π/N)kn}

A voice signal contains frequencies up to 4 kHz. Determine the Nyquist sampling rate.

Discuss radix-2 Decimation in Time FFT algorithm.

Compare DFT and FFT with respect to computational efficiency.

Find the 4-point DFT of the sequence:
x[n] = {1,0,1,0}

FIR filter design

IIR filter design

Discrete time sinusoidal signals.

Frequency domain representation of LTI Systems