In physics, quantization is the process of explaining a classical understanding of physical phenomena in terms of a newer understanding known as "quantum mechanics". It is a procedure for constructing a quantum field theory starting from a classical field theory. In digital signal processing, quantization is the process of approximating ("mapping") a continuous range of values (or a very large set of possible discrete values) by a relatively small ("finite") set of ("values which can still take on continuous range") discrete symbols or integer values. In digital music processing technology, quantization is the process of aligning a set of musical notes to a precise setting. This results in notes being set on beats and on exact fractions of beats. Quantization, involved in image processing, is a lossy compression technique achieved by compressing a range of values to a single quantum value. When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible. In linguistics, a quantized expression is such that, whenever it is true of some entity, it is not true of any proper subparts of that entity. Example: If something is an "apple", then no proper subpart of that thing is an "apple".
The principle that the electric charge of an object must equal an integral multiple of a universal basic charge.
The various properties of electric charge :1.Additivity of charges2.Charge is conserved3.Quantization of charge
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.
physical examples are examples of thing or changes or transformations which you can see with you eyes or hold with your hands.
Sampling Discritizes in time Quantization discritizes in amplitude
The ideal Quantization error is 2^N/Analog Voltage
one syllable LOL
There are two types of quantization .They are, 1. Truncation. 2.Round off.
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
theory were all proved by taking longer and longer sequences of inputs. This indicates that a quantization strategy that works with sequences or blocks of output would provide some improvement in performance over scalar quantization. In other words, we wish to generate a representative
assigning too few quantization intervals during sampling of the signal
reduces