assigning discrete integer values to PAM sample inputs
Encoding the sign and magnitude of a quantization interval as binary digits
Quantization range refers to the range of values that can be represented by a quantization process. In digital signal processing, quantization is the process of mapping input values to a discrete set of output values. The quantization range determines the precision and accuracy of the quantization process.
Sampling Discritizes in time Quantization discritizes in amplitude
one syllable LOL
The ideal Quantization error is 2^N/Analog Voltage
There are two types of quantization .They are, 1. Truncation. 2.Round off.
Mid riser quantization is a type of quantization scheme used in analog-to-digital conversion where the input signal range is divided into equal intervals, with the quantization levels located at the midpoints of these intervals. This approach helps reduce quantization error by evenly distributing the error across the positive and negative parts of the signal range.
Compressing a voice signal sample into segments prior to quantization and expanding it it its original size once transmitted Compressing larger signals more than smaller signals
Quantization noise is a model of quantization error introduced by quantization in the analog-to-digital conversion(ADC) in telecommunication systems and signal processing.
quantisation noise decrease and quantization density remain same.
You get Jaggies
Vector quantization lowers the bit rate of the signal being quantized thus making it more bandwidth efficient than scalar quantization. But this however contributes to it's implementation complexity (computation and storage).
Most people aren't aware of it because a) the quanta are extremely small and b) they don't know what to look for. However, if you do know what to look for, there are ways to observe it without any fancy equipment... the most recent quantization phenomenon I noticed was the way fluorescent light was refracting off of a CD.