Quantization Error Of 12-bit Adc
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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 quantization error formula adc reconstructed signal (red). The difference between the original signal and the reconstructed
Adc Quantization Noise
signal is the quantization error and, in this simple quantization scheme, is a deterministic function of the input signal.
Adc Channels
Quantization, 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 Noise In Pcm
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 quantization error example 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 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 l
In electronics, an analog-to-digital converter (ADC, A/D, A–D, or A-to-D) is a system that converts an analog signal, such as a sound picked up by a microphone or light entering a digital camera, into a digital signal. An ADC may also provide an isolated measurement quantization error in analog to digital conversion such as an electronic device that converts an input analog voltage or current to a quantization of signals digital number proportional to the magnitude of the voltage or current. Typically the digital output is a two's complement binary number that what is quantization is proportional to the input, but there are other possibilities. There are several ADC architectures. Due to the complexity and the need for precisely matched components, all but the most specialized ADCs are implemented as integrated circuits https://en.wikipedia.org/wiki/Quantization_(signal_processing) (ICs). A digital-to-analog converter (DAC) performs the reverse function; it converts a digital signal into an analog signal. Contents 1 Explanation 1.1 Resolution 1.1.1 Quantization error 1.1.2 Dither 1.1.3 Non-linearity 1.2 Jitter 1.3 Sampling rate 1.3.1 Aliasing 1.3.2 Oversampling 1.4 Relative speed and precision 1.5 Sliding scale principle 2 Types 2.1 Direct-conversion 2.2 Successive approximation 2.3 Ramp-compare 2.4 Wilkinson 2.5 Integrating 2.6 Delta-encoded 2.7 Pipeline 2.8 Sigma-delta 2.9 Time-interleaved 2.10 Intermediate FM stage https://en.wikipedia.org/wiki/Analog-to-digital_converter 2.11 Other types 3 Commercial 4 Applications 4.1 Music recording 4.2 Digital signal processing 4.3 Scientific instruments 4.4 Rotary encoder 5 Electrical symbol 6 Testing 7 See also 8 Notes 9 References 10 Further reading 11 External links Explanation[edit] The conversion involves quantization of the input, so it necessarily introduces a small amount of error. Furthermore, instead of continuously performing the conversion, an ADC does the conversion periodically, sampling the input. The result is a sequence of digital values that have been converted from a continuous-time and continuous-amplitude analog signal to a discrete-time and discrete-amplitude digital signal. An ADC is defined by its bandwidth and its signal-to-noise ratio. The bandwidth of an ADC is characterized primarily by its sampling rate. The dynamic range of an ADC is influenced by many factors, including the resolution, linearity and accuracy (how well the quantization levels match the true analog signal), aliasing and jitter. The dynamic range of an ADC is often summarized in terms of its effective number of bits (ENOB), the number of bits of each measure it returns that are on average not noise. An ideal ADC has an ENOB equal to its resolution. ADCs are chosen to match the bandwidth and required signal-to-noise ratio of the signal to be quantized. If an ADC operates at a sampling rate
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