Quantization Error Probability Density Function
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the original analog signal (green), the quantized signal (black dots), the signal reconstructed from the quantized signal (yellow) and the difference between the original signal and the reconstructed quantization error formula signal (red). The difference between the original signal and the reconstructed signal quantization error definition is the quantization error and, in this simple quantization scheme, is a deterministic function of the input signal. Quantization, quantization error example in mathematics and digital signal processing, is the process of mapping a large set of input values to a (countable) smaller set. Rounding and truncation are typical examples of quantization processes.
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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 algorithmic function that quantization example performs quantization is called a quantizer. An analog-to-digital converter is an example of a quantizer. Contents 1 Basic properties of quantization 2 Basic types of quantization 2.1 Analog-to-digital converter (ADC) 2.2 Rate–distortion optimization 3 Rounding example 4 Mid-riser and mid-tread uniform quantizers 5 Dead-zone quantizers 6 Granular distortion and overload distortion 7 The additive noise model for quantization error 8 Quantization error models 9 Quantization noise model 10 Rate–distortion quantizer design 11 Neglecting the entropy constraint: Lloyd–Max quantization 12 Uniform quantization and the 6 dB/bit approximation 13 Other fields 14 See also 15 Notes 16 References 17 External links Basic properties of quantization[edit] Because quantization is a many-to-few mapping, it is an inherently non-linear and irreversible process (i.e., because the same output value is shared by multiple input values, it is impossible in general to recover the exact input value when given only the output value). The set of possible input values may be infinitely large, and may possibly be continuous and therefore uncountable (such as the set of all real numbers, or all real numbers within some limited range). The set of possible
från GoogleLogga inDolda fältBöckerbooks.google.se - Well established in the consumer electronics industry, Digital Audio Signal Processing (DASP) techniques are used quantization level in audio CD, computer music and DAT components. In
Quantization Step Size Formula
addition the applications afforded by this versatile technology now range from real-time signal
How To Reduce Quantization Error
processing to room simulation. Grounding...https://books.google.se/books/about/Digital_Audio_Signal_Processing.html?hl=sv&id=IPMhDE-QWzQC&utm_source=gb-gplus-shareDigital Audio Signal ProcessingMitt bibliotekHjälpAvancerad boksökningSkaffa tryckt exemplarInga e-böcker finns tillgängligaWiley.comAmazon.co.ukAdlibrisAkademibokandelnBokus.seHitta boken i ett bibliotekAlla försäljare»Handla böcker https://en.wikipedia.org/wiki/Quantization_(signal_processing) på Google PlayBläddra i världens största e-bokhandel och börja läsa böcker på webben, surfplattan, mobilen eller läsplattan redan idag.Besök Google Play nu »Digital Audio Signal ProcessingUdo ZölzerJohn Wiley & Sons, 15 dec. 1997 - 279 sidor 0 Recensionerhttps://books.google.se/books/about/Digital_Audio_Signal_Processing.html?hl=sv&id=IPMhDE-QWzQCWell established in the consumer electronics industry, https://books.google.se/books?id=IPMhDE-QWzQC&pg=PA28&lpg=PA28&dq=quantization+error+probability+density+function&source=bl&ots=RjoxD0OMdF&sig=4AtuT-HskU0v86ppL5Cxa4MAfv0&hl=en&sa=X&ved=0ahUKEwi634Wi2OnPAhUDkiwKHa8kCf0Q Digital Audio Signal Processing (DASP) techniques are used in audio CD, computer music and DAT components. In addition the applications afforded by this versatile technology now range from real-time signal processing to room simulation. Grounding the theoretical foundations of DASP in terms of practical applications, this book gives meaning to the mathematical concepts behind this subject area. It includes detailed accounts of: AD/DA conversion and DSP systems Digital Transmission Systems and M-PEG audio coding Studio technology and electronic storage media Audio algorithms: equalization, dynamic range control, room simulation and sampling rate conversion For Audio and Communications Engineers this book provides a thorough coverage of the technical basis of DASP. For Research Students in Signal Processing or Applied Physics it transforms erudite audio signal processing theory into tangible conc
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