An analog signal must be converted to a digital one for it to be stored and manipulated by a computer. The process is called analogue to digital conversion.
During this process the analog signal is sampled at a rate less than twice the highest frequency contained in the signal. This produces a distorted digital representation of the signal known as aliasing.
Analog to Digital Conversion
An analog-to-digital converter (also called ADC, A to D or ADC) converts an analog signal, such as a voltage or current, into a digital representation. This allows us to store and manipulate the data in a computer system for further processing. Analog to digital conversion is a crucial component in most real world measurement systems. For example, the signals generated by physiological sensors such as electroencephalograms, electrocardiograms or electrooculograms can be converted into digital form for further processing with the help of an ADC.
An ADC converts the analog signal into a series of binary numbers which are then compared to each other to produce an output signal which is a valid piece of data. This process is known as quantization. As the number of bits increases, the amount of quantization error decreases and it becomes possible to represent more of the original signal within the limited space of the digital code, such as when converting vhs tapes to digital format.
This process is not without its problems however. For example, the digital code must be sampled at a rate which is at least twice as fast as the maximum frequency of the analog signal (the Nyquist sampling theorem). This is because if we try to represent an analog signal using a lower number of bits than what is required for the Nyquist sample rate, we will introduce digital artifacts which are not desirable in the final result.
Fortunately, some methods of A/D conversion can reduce or even eliminate some of the quantization error which can occur. For example, if the ADC is oversampled, the quantization error can be forced out of band, making it less noticeable. The use of dither is also a good way to hide quantization error in an analog signal.
ADCs are commonly found in electronic devices such as microphones, telecommunications equipment and digital cameras. They are used to convert the analog electrical signals that represent physical quantities such as sound, light, pressure or temperature into digital information that can be processed by computers and other digital devices. The process of A/D conversion is a fundamental technology that has allowed the world to move away from relying on largely mechanical and analog technology towards the digitized world we now live in.
Analog to Digital Converters
Analog to digital converters are electronic integrated circuits that convert analog signals such as voltages into a flow of binary values representing ones and zeros. They are the key to making any measurable analog physical quantity into usable digital data for processing by digital systems like microcontrollers and computer processors. Just about every measurable environmental parameter in the world comes in an analog form that requires an A/D converter to convert it into digital form. For example, a temperature monitoring system needs an A/D converter to transform analog input data into digital output that can be read and understood by a computer.
The conversion process begins with a clock signal that provides a start condition. The A/D converter then samples the analog input signal at discrete points in time, called sampling intervals. The rate at which these values are sampled is called the A/D conversion rate or sampling frequency. The mathematical theory behind the A/D conversion process states that a continuous varying analog signal can be faithfully reproduced from its sampled digital values using a suitable reconstruction filter. This is known as the Nyquist Sampling Theorem.
Each of the A/D sampled amplitude axis values is then converted into a binary number using an A/D encoder. The coded data is then stored as an uncompressed digital file or digitized in a memory array. The resulting digitized information can be reproduced an infinite number of times without losing quality.
A digital to analog converter is a complex piece of electronics. In fact, the higher the resolution (bit depth), the more comparators are needed in an A/D converter and the more complex the A/D circuit becomes. For instance, a 4-bit A/D would require 15 (24) comparators while an 8-bit A/D requires 1023 (91) comparators.
Another factor to consider when choosing an A/D is its noise and distortion performance, which is generally expressed as a signal-to-noise ratio (SINAD) or signal-to-distortion ratio (SNR). A/D performance degrades rapidly at frequencies near the Nyquist sampling limit so look for a graph in its data sheet that shows ENOB at various frequencies versus the input signal frequency.
Analog to Digital Processors
The analog-to-digital converter converts an analog signal that varies continuously in time and amplitude into a multilevel digital signal that can be stored and transmitted. This is one of the most critical steps that allowed us to begin relying less on largely analog or mechanical technology and more on digitized data that can be easily stored, transmitted and processed by computers.
Analog inputs typically come from sensors that measure physical quantities such as sound, light, temperature or motion. To make this data available to a computer, the analog signal needs to be converted into a digital form that the microcontroller can read. This process is known as an analog-to-digital conversion or ADC.
In order to convert an a continuous signal into a digital signal, the input needs to be sampled on a regular basis. The frequency of this sampling needs to be higher than the highest measurable frequency in the original analog signal, or else you will get an artifact called aliasing. Ideally, the sampling rate is twice as high as the highest possible frequency contained in the analog input.
As each snapshot of the analog amplitude is taken at the sampling rate, the resulting bits need to be shifted into place in a sequence of binary values, which must be arranged in a specific manner in order for the computer to be able to read them as valid numbers. The number of bits needed to represent an amplitude can be defined by the amount of bit resolution or bit depth that is required, and higher bit resolutions allow for less quantization error (which is why some recordings made with 8-bit resolutions tend to sound noisy).
Once all of this digitized data has been represented as a set of integer values, it can be arranged and copied an infinite number of times without losing any information, making it great for storage in memory and transmission over long distances. It also makes it ideal for processing by a digital signal processor, which can perform a multitude of mathematical operations on the data.
The ADC is a vital part of most modern electronic devices, from cameras to computer chips. In fact, most of the hardware inside a laptop or smartphone includes an analog-to-digital converter. Standalone hardware audio interfaces like those used in music production also include high-quality ADCs.
Analog to Digital Encoders
Analog signals are continuous in time and amplitude, while digital signals are discrete values. In order to use analog data in a computer, it must be converted to a digital signal, which is a series of numbers that can be stored in memory or transmitted over the internet. Analog-to-Digital converters, also known as ADC’s, are the electronic circuits that perform this function.
To convert an analog signal into a digital signal, the ADC must sample the signal at regular intervals of time — this is called sampling — and then encode the samples into a sequence of binary numbers. The number of bits used to represent the analogue input voltage is called the ADC resolution. A higher resolution results in a more accurate representation of the analog input.
A sample rate that is too low won’t accurately depict the original signal; it will create aliasing and introduce distortion. A sample rate that is too high, however, can cause the ADC to use more resources and can even overflow its internal registers.
To avoid these problems, the ADC must sample at a rate that is at least twice the highest frequency present in the analog signal. This is the Nyquist sampling rate.
The sampled amplitude data is then stored as a series of digital numbers, with each bit carrying more weight than the previous one. In a typical encoding scheme, the MSB (most significant bit) is given a weight of 1, while the LSB is given a weight of -1. This yields a sequence of numbers that can be converted back to an amplitude signal using the inverse of a logarithm.
The digital representation of the analog signal can be copied and transmitted an infinite number of times without any loss in quality, making it a valuable tool for modern electronic devices. Analog-to-Digital converters are commonly found in many different types of consumer electronics, from laptops to mobile phones and even standalone hardware audio interfaces used for music production. In addition, the ADC process is critical to the operation of many industrial and military sensors that measure analog signals such as temperature, pressure, and flow.
