Quantizing Error Audio
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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 signal (red). The difference between the original quantization error definition signal and the reconstructed signal is the quantization error and, in this simple quantization
Quantization Error Formula
scheme, is a deterministic function of the input signal. Quantization, in mathematics and digital signal processing, is the process of mapping how to reduce quantization error a large set of input values to a (countable) smaller set. Rounding and truncation are typical examples of quantization processes. Quantization is involved to some degree in nearly all digital signal processing, as the process quantization error in pcm 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 performs quantization is called a quantizer. An analog-to-digital converter is an example of a quantizer. Contents 1 Basic properties of quantization 2
Quantization Error Example
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 output values may be finite or countably infinite. The input and output sets involved in quantization can be defined in a rather general way. For example, vector quantization is the application of quantization to multi-dimensional (vector-valued) input data.[1] Basic types of quantization[edit] 2-bit resolution w
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effects - an audio demonstration David Dorran SubscribeSubscribedUnsubscribe6,7596K Loading... Loading... Working... Add to Want to watch this again later? Sign in to https://www.youtube.com/watch?v=fUHbcGNJhVM add this video to a playlist. Sign in Share More Report Need to report the video? Sign in to report inappropriate content. Sign in Transcript Statistics 744 views 6 Like this video? Sign in to make your opinion count. Sign in 7 0 Don't like this video? Sign in to make quantization error your opinion count. Sign in 1 Loading... Loading... Transcript The interactive transcript could not be loaded. Loading... Loading... Rating is available when the video has been rented. This feature is not available right now. Please try again later. Uploaded on Jun 10, 2011Demostrates the effects of quantisation using an audio example Category quantization error in Education License Creative Commons Attribution license (reuse allowed) Show more Show less Loading... Advertisement Autoplay When autoplay is enabled, a suggested video will automatically play next. Up next Quantisation Error during discrete signal capture - video 2 - Duration: 10:07. David Dorran 1,523 views 10:07 DSP Lecture 23: Introduction to quantization - Duration: 1:03:51. Rich Radke 8,100 views 1:03:51 Discrete Systems 1.30 - practice - implementing a discrete system in matlab - Duration: 10:01. David Dorran 2,477 views 10:01 Quantisation Error during discrete signal capture - video 1 - Duration: 10:07. David Dorran 1,040 views 10:07 Quantization Part 2: Quantization Understanding - Duration: 4:08. Madhan Mohan 15,150 views 4:08 Quantisation Error Explained for discrete signal capture - Duration: 13:53. David Dorran 2,640 views 13:53 Digital Audio 102 - PCM, Bit-Rate, Quantisation, Dithering, Nyquists Sampling Theorum - PB15 - Duration: 6:06. Production Bytes 61,615 views 6:06 Analysis of Quantization Error - Duration: 15:0