In real world, all signals like
light, sound etc, are analog signals. These signals have to be
converted into digital form so that they can be manipulated by
digital equipment. Device used to convert analog signal into digital
signal is called Analog to Digital Converter (ADC). An example of an analog to digital converter is a Scanner –
It takes a picture (analog) as input and convert into digital picture. ADC is
an electrical circuit that converts continuous time and continuous
amplitude signal into discrete time and discrete amplitude signal.
Let us first discuss basic concept of analog to digital conversion. The process of digitizing the domain(time) is called sampling and the process of digitizing range(voltage/current) is called quantization.
Let us first discuss basic concept of analog to digital conversion. The process of digitizing the domain(time) is called sampling and the process of digitizing range(voltage/current) is called quantization.
Sampling
: An ADC circuit samples analog signal from time to time. Then, each sample is converted into a number based on its voltage level.
The frequency at which sampling occurs is called sampling rate or
sampling frequency. e.g if sampling frequency is 22000 Hz, it means, in
one second 22000 input points will be sampled and distance between
two adjacent time points is 1/22000 seconds. Higher the sampling
frequency, more perfect will be the analog signal produced by DAC
(when it is required to reconstruct the analog signal from digital
samples). But more memory will be needed to store these samples. So
there is always a trade off between memory required to store samples
and accuracy of signal. But to reproduce analog signal from digital
samples, there should be some minimum number of samples. And
According to Nyquist sampling
theorem, sampling rate must be at least twice the highest
frequency component to avoid aliasing.
Fs = 2Fmax
Quantization: Quantization is the process of converting continuous value signal into discrete value signal so that signal takes only finite set of values. Unlike sampling (where we saw that under some conditions, it is possible to reconstruct the signal), quantization results in some loss of information called quantization error. One of basic choice in quantization is the number of discrete quantization levels to use. Fundamental tradeoff in this choice is the resulting signal quality vs data(bits) needed to represent each sample. With L levels, number of bits required to represent each level,
Range(EFSR)
: Range of ADC circuit is the difference between highest and
lowest input voltage the ADC device can take in as input.
EFSR = Vmax
- Vmin
Resolution – Resolution of ADC is defined as minimum change in input analog voltage to guarantee a change in output code level.
Resolution of ADC, Q = EFSR / (2N – 1) where,
N = Number of bits
Higher the number of bits, lesser is
the resolution and higher is accuracy.
For Example,
Let us say Range of ADC is 10 V and number of bits are 5; hence, total number of voltage levels are 32. Each level represents/resolution is 10/32 = 0.3125 V; i.e., any change is input voltage less than 0.3125 won't result in any change in output.
Flash ADC (named because of its high speed) : Flash ADC is
also known as direct conversion ADC. It uses linear voltage ladder with
comparator at each step of ladder to compare input analog voltage to
successive reference voltage. Often, this comparator ladder requires
many resistors. For an N-bit converter, 2N - 1 comparators are
required. Reference voltage for each comparator is one least significant
bit greater than its preceding comparator. Each comparator produces
result 1 if analog voltage is greater than reference voltage. It means
if input voltage is between Vx4 and Vx5, then, comparators 0-4 produces
1 and remaining comparators produces 0.
From Here, we can also say that resolution of ADC is difference
between reference voltages of two adjacent comparators.
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| N-bit Flash ADC converter |
Nicely explained. :)
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