Which type of quantization is better?

Explanation: According to signal to noise level ratio non uniform quantization provides better quantization for weak signals.

1. Which is better uniform or non uniform quantization?
2. Why non uniform quantization is better than uniform quantization?
3. Why do we prefer non uniform quantization?
4. What is quantization and its types?

Which is better uniform or non uniform quantization?

The nonuniform quantization strategy for compressing neural networks usually achieves better performance than its counterpart, i.e., uniform strategy, due to its superior representational capacity.

Why non uniform quantization is better than uniform quantization?

Another important difference between uniform and nonuniform quantization is that, in the uniform quantization, some amount of quantization error can happen, but nonuniform quantization reduces the quantization error. Communication systems send signals from the transmitter to the receiver.

Why do we prefer non uniform quantization?

The technique of non-uniform quantization described in the paper is readily implemented to improve the steady state accuracy of an existing system, or alternatively for a given design-consistent accuracy, to economize in analogue-to-digital converter bit capacity.

What is quantization and its types?

Quantization, in mathematics and digital signal processing, is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often with a finite number of elements. Rounding and truncation are typical examples of quantization processes.