- Uniform quantizer
- Non-uniform quantizer
- Uniform & Non uniform quantizer
- None of the mentioned
Explanation: The output SNR (Signal-to-Noise Ratio) can be made independent of the input signal level by using a non-uniform quantizer. Non-uniform quantization techniques, such as logarithmic or companding quantization, allocate more quantization levels to smaller amplitude values, which improves the representation of weak signals and reduces the quantization noise. In non-uniform quantization, the step size is variable and depends on the signal amplitude, allowing for better performance across a wide range of input signal levels.
In contrast, uniform quantization divides the range of the continuous amplitude signal into equal-sized intervals or steps, assigning each interval a discrete amplitude value. This type of quantization works well for strong signals but results in a poorer SNR for weak signals, as the quantization error can be relatively high compared to the signal amplitude.
Example: The μ-law and A-law companding techniques are commonly used non-uniform quantization methods in telecommunication systems for audio signal compression. These methods allocate more quantization levels to lower-amplitude signals, which improves the representation of weak signals and reduces the quantization noise.
Facts:
- Non-uniform quantization techniques can achieve a more consistent SNR performance across a wide range of input signal levels compared to uniform quantization.
- Non-uniform quantization is particularly suitable for signals with a large dynamic range or when the input signal levels vary significantly.
Relevant Stats: Using non-uniform quantization, such as μ-law or A-law companding, can provide a significantly higher SNR for weak signals compared to uniform quantization. For instance, the μ-law companding can provide an SNR of around 34 dB for weak signals, which is a considerable improvement compared to uniform quantization.
In summary, the output SNR can be made independent of the input signal level by using a non-uniform quantizer, as it allocates quantization levels more effectively across the entire range of signal amplitudes, providing improved representation and reduced quantization noise for both weak and strong signals.