Maximum Quantization Error Example
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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
Quantization Error Formula
the original signal and the reconstructed signal is the quantization error and, in this quantization error in pcm simple quantization scheme, is a deterministic function of the input signal. Quantization, in mathematics and digital signal processing, is the
How To Reduce Quantization Error
process of mapping 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 quantization error in a/d converter 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 performs quantization is called a quantizer. An analog-to-digital converter is an example of a quantizer. Contents quantization error percentage 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 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
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Quantization Error In Dsp
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Quantization Step Size Formula
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Help Rules Groups Blogs What's New? Teardown Videos Datasheets Advanced Search Forum EDA Theory Elementary Electronic Questions How do I solve quantization errors in ADC system? + Post New Thread Results 1 to 8 of 8 How do I solve quantization errors in ADC system? LinkBack LinkBack URL About http://www.edaboard.com/thread40731.html LinkBacks Thread Tools Show Printable Version Download This Thread Subscribe to this Thread… Search Thread Advanced Search 22nd June 2005,16:25 #1 KrisUK Newbie level 4 Join Date May 2005 Posts 7 Helped 0 / 0 Points 1,398 Level 8 How do I solve quantization errors in ADC system? How do I work out quantization error in a ADC system? I looked around on different sites from a recommendation from another user and came to the conclusion it is the max voltage divided by the quantization error number of bits. Is this correct? Thank you. 22nd June 2005,16:25 22nd June 2005,16:52 #2 Kral Advanced Member level 4 Join Date Mar 2005 Location USA Posts 1,326 Helped 278 / 278 Points 11,626 Level 25 Re: Quantization Error The weighting of the LSB is equal to the (Reference Voltage)/2^n, where n is the number of bits. The Quantization error = 1/2 LSB. If the ADC is bipolar (can represent both positive and negative values, then the LSB weighting is 2X the above value. quantization error in The quantization error is still 1/2 LSB. The total error includes the quantization error plus scale factor (gain) error, non-linearity errors. Regards, Jon 22nd June 2005,16:52 22nd June 2005,17:22 #3 banh Advanced Member level 1 Join Date Dec 2004 Posts 458 Helped 17 / 17 Points 3,856 Level 14 Quantization Error quantization error/noise is the difference between the actual sampled value and the quantized value. 2 cases: if the the actual sampled value is between 2 quantized levels -> it will either be rounded off or truncated. rounding -> take the nearest quantized level. truncated -> take the level below it. hence: the error is - rounding off: - truncated where Q is the resolution. Last edited by BlackMamba; 27th August 2010 at 12:44. 22nd June 2005,17:22 22nd June 2005,18:42 #4 KrisUK Newbie level 4 Join Date May 2005 Posts 7 Helped 0 / 0 Points 1,398 Level 8 Re: Quantization Error Well, say I had a 3 bit ADC with a max of 8V; what would the max quantization error be? Would it be 8/8 = 1V ? Or say a 10 bit ADC with a max of 5V: 5/1024 = 0.0048828125V (or 4.88mV) ? I don't really need to know the theory behind it, just how to work it out for an exam I've got coming up. 22nd June 2005,18:49 #5 banh Advanced Member level 1 Join Date Dec 2004 Posts 458 Helped 17 / 17 Points 3,856 Level 14 Quantization Error assuming you're using round-off. so i