The term "quantized" means, is divided into discreet sections which are indivisible; or in other words, it is made of small sections that cannot be made into even smaller sections. In the science of quantum mechanics, it turns out that matter, energy, space and time are all quantized. There is a smallest quantity of each of these which cannot be subdivided into an even smaller quantity. One of these tiny, indivisible pieces would be called a quantum.
reduces
problem with uniform quantisatonis 1.real audio signal is concentrated near zero 2.human ear is more sensitive to quantisaton error at small value using non-uniform quantisaton quantisaton intrval smaller near zero Non uniform quantization reduces the signal-noise ratio at low signal levels.
A quantizer with output as zero when input is zero s mid tread while one which shows change/ transitition in level at input 0 is mid riser
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.
one syllable LOL
The ideal Quantization error is 2^N/Analog Voltage
Sampling Discritizes in time Quantization discritizes in amplitude
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.
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).
assigning discrete integer values to PAM sample inputs Encoding the sign and magnitude of a quantization interval as binary digits
If the sampling frequency doubles, then the quantization interval remains the same. However, with a higher sampling frequency, more quantization levels are available within each interval, resulting in a higher resolution and potentially improved signal quality.