page_title: Quantization (signal processing)
section_title: Types
hierarchical_section_title: Quantization (signal processing) / Types
caption_attribution_description: English: 2-bit resolution with four levels of quantization, compared with an analog sine wave. Corrected from five level image in source: Hodgson, Jay (2010). Understanding Records, p.56. ISBN&#160;978-1-4411-5607-5. He adapted from Franz, David (2004). Recording and Producing in the Home Studio, p.38-9. Berklee Press.
context_page_description: Quantization, in mathematics and digital signal processing, is the process of mapping input values from a large set to output values in a smaller set, often with a finite 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 is referred to as quantization error. A device or algorithmic function that performs quantization is called a quantizer. An analog-to-digital converter is an example of a quantizer.
caption: 2-bit resolution with four levels of quantization compared to analog.[8]
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