4.1. To explain how the signal
4.1. To explain how the signal dynamic range is related with thenumber of bits in codewords.
4.2. Analyse the linear quantization characteristic, parameters,features.
4.3. Analyse the nonlinear quantization characteristic,parameters features.
(4.1) Signal dynamic range is the ratio of the largest signalthat exists to the noise present when no signal exists. Theydescribe the ratio between the largest representable number to thequantization error.
Some of the comparison of codewords in bits with signal dynamicrange is given below.
|16-bit Audio Converters
|90 to 95 dB
|18-bit Audio Converters
|20-bit Audio Converters
|24-bit Audio Converters
|110 to 120 dB
Dynamic Range = Peak Level – Noise Floor in dB
An n bit data word yields 2n quantization levels.
Further, dynamic range(dB)=6.02n+1.76 dB=6n(nearly).
(4.2 and 4.3) Quantization is the process of mapping inputvalues from a large continuous set to output values in a smallerfinite set. Eg:- Rounding and truncation.
With linear quantization, every increment in the sampled valuecorresponds to a fixed size increment, independent of the actualsignal amplitude. Here, the signal to noise ratio is large for highlevels but small for low level signals. The quantizing intervalsare of equal size.
With non-linear quantization, there is generally some sort oflogarithmic encoding, so that the increment for small sample valuesis much smaller than the increment for large sample values. Thestep size should be almost proportional to the sample size. Thus,S/N ratio due to quantization noise, is regardless of the signalamplitude. We can use fewer bits to get a given S/N ratio over thesignal amplitude range of interest.