Question on discrete signals and quantization

1. Why does quantization distort a signal?
2. What are two types of quantization errors?
3. What is relationship between quantization levels and no of bits?
4. Why quantization is needed in digital signal processing?

Why does quantization distort a signal?

At lower amplitudes the quantization error becomes dependent on the input signal, resulting in distortion. This distortion is created after the anti-aliasing filter, and if these distortions are above 1/2 the sample rate they will alias back into the band of interest.

What are two types of quantization errors?

2.11 Quantization in Digital Filters. Quantization errors in digital filters can be classified as: Round-off errors derived from internal signals that are quantized before or after more down additions; Deviations in the filter response due to finite word length representation of multiplier coefficients; and.

What is relationship between quantization levels and no of bits?

Each quantisation level is represented by a unique binary number. The number of levels is therefore related to the number of bits, n, used in the binary numbers that represent the quantisation levels. For example, using 3 bits provides eight (2³) discrete levels represented by: 000, 001, 010, …, 111.

Why quantization is needed in digital signal processing?

The conversion of a waveform into a set of digital signals starts with quantization of the wave to produce a set of numbers. The greater the number of quantization levels, the more precise the digital representation, but excessive quantization is wasteful in terms of the time required.