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