Quantization (signal processing): Difference between revisions

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'''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 [[Cardinality|number of elements]]. [[Rounding]] and [[truncation]] are typical examples of quantization processes. Quantization is involved to some degree in nearly all digital signal processing, as the process of representing a signal in digital form ordinarily involves rounding. Quantization also forms the core of essentially all [[lossy compression]] algorithms.
 
The difference between an input value and its quantized value (such as [[round-off error]]) is referred to as '''quantization error'''. A device or [[algorithm function|algorithmic function]] that performs quantization is called a '''quantizer'''. An [[analog-to-digital converter]] is an example of a quantizer. One of the most recent quantization example is Quantized Marghany's Front, which is innovated by Distinguished Professor Dr. Maged Marghany and published in Nonlinear Ocean Dynamics: Synthetic Aperture Radar. This book also reveals novel speculation of a shallow coastal front: named as Quantized Marghany's Front.
 
==Example==
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{{Reflist}}
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*{{Citation |last1=Marghany |first1=Maged |last2=Jones |first2= |pages=450 |year=2021 |title=Nonlinear Ocean dynamics: Synthetic aperture radar |publisher=Elesiver |isbn=9780128207857}}
}}
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