Digital Signal Processing Basics
  • 1. What is the purpose of digital signal processing?
A) To process images using analog technology
B) To create music using traditional instruments
C) To analyze and modify signals using digital systems
D) To store signals in physical media
  • 2. What is a discrete signal in digital signal processing?
A) A signal that changes smoothly over time
B) A continuous signal with infinite values
C) A signal defined at discrete time points
D) A signal that amplifies quickly
  • 3. Which of the following is an example of a digital filter?
A) Optical lens filter
B) Analog voltage regulator
C) Mechanical water filter
D) Finite Impulse Response (FIR) filter
  • 4. What is the purpose of the Fast Fourier Transform (FFT) in digital signal processing?
A) To convert analog signals to digital signals
B) To efficiently compute the frequency components of a signal
C) To store signals in a database
D) To amplify the signal power
  • 5. What is the role of a Digital Signal Processor (DSP) in digital signal processing?
A) To perform mathematical operations on digital signals
B) To analyze physical vibrations
C) To generate random noise signals
D) To convert analog signals to digital signals
  • 6. What is the Nyquist-Shannon sampling theorem in digital signal processing?
A) It determines the color of digital signal displays
B) It calculates the signal-to-noise ratio of a signal
C) It predicts the lifetime of digital signal processors
D) It states that a signal should be sampled at twice its highest frequency
  • 7. Which mathematical operation is commonly used for digital signal filtering?
A) Square root
B) Exponential growth
C) Convolution
D) Trigonometry
  • 8. What is Quantization in digital signal processing?
A) Assigning discrete levels to continuous signal values
B) Creating random signal patterns
C) Doubling the amplitude of a signal
D) Reducing the number of samples in a signal
  • 9. What is the purpose of applying a window function in digital signal processing?
A) To amplify high-frequency noise
B) To create reverberation effects
C) To reduce spectral leakage in Fourier analysis
D) To increase signal distortion
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