Revision - Signal Processing

Revision

1. Signal processing deals with analysis and modification of signals to improve quality and extract information.
2. In communication, it is used to remove noise, improve quality, compress data, and convert analog ↔ digital.
3. Filtering removes unwanted frequencies (LPF, HPF, BPF, Notch).
4. Amplification increases signal strength without changing its shape (avoids distortion).
5. Sampling converts analog (continuous-time) signal to discrete-time signal.
6. Nyquist Theorem: fs ≥ 2 fmax​ for correct reconstruction.
7. If fs < 2 fmax ​, aliasing occurs and causes distortion.
8. Anti-aliasing LPF is used before sampling to prevent aliasing.
9. Quantization converts sample amplitudes into finite discrete levels.
10. Quantization introduces quantization error (noise).
11. More bits per sample → better quality but higher data rate.
12. Encoding converts quantized values into binary (0s and 1s); PCM = Sampling + Quantization + Encoding.

Q&A

1. What is signal processing?

Signal processing is the field that deals with analyzing, modifying, and manipulating signals to improve their quality or to extract useful information.

2. Why is signal processing needed in communication systems?

It is needed to remove noise, reduce distortion, improve signal quality, compress data, and convert signals between analog and digital forms.

3. What is filtering?

Filtering is the process of removing unwanted frequency components from a signal and keeping only the required frequencies.

4. Name the types of filters used in signal processing.

The main types of filters are Low Pass Filter (LPF), High Pass Filter (HPF), Band Pass Filter (BPF), and Notch Filter.

5. What is the function of an amplifier?

An amplifier increases the strength (amplitude) of a weak signal without changing its shape.

6. What is sampling?

Sampling is the process of converting a continuous-time (analog) signal into a discrete-time signal by taking values at regular intervals.

7. State Nyquist Sampling Theorem.

The sampling frequency must be at least twice the highest frequency present in the signal, i.e., fs ≥ 2fmax.

8. What is aliasing?

Aliasing is a distortion that occurs when the sampling frequency is less than twice the highest frequency of the signal, causing high frequencies to appear as low frequencies.

9. How can aliasing be prevented?

Aliasing can be prevented by using an anti-aliasing low-pass filter before sampling and by sampling at or above the Nyquist rate.

10. What is quantization?

Quantization is the process of converting continuous-amplitude sampled values into a finite number of discrete amplitude levels.

11. What is quantization error?

Quantization error is the difference between the actual sample value and the quantized value, and it appears as quantization noise.

12. How does the number of bits affect quantization?

More bits reduce quantization error and improve quality, while fewer bits increase error and reduce signal quality.

13. What is encoding?

Encoding is the process of converting quantized sample values into binary form (0s and 1s).

14. Why is encoding necessary?

Encoding is necessary because digital systems can store, process, and transmit only binary data, and binary signals are more reliable in the presence of noise.

15. What is PCM (Pulse Code Modulation)?

PCM is a digital signal representation technique in which an analog signal is sampled, quantized, and encoded into binary form.

16. Where is PCM used?

PCM is used in digital telephony, audio CDs, and digital audio communication systems.

17. Write the steps involved in PCM.

The steps involved in PCM are Sampling, Quantization, and Encoding.

18. What is an anti-aliasing filter?

An anti-aliasing filter is a low-pass filter used before sampling to remove high-frequency components and prevent aliasing.