For ADCs, performance can generally be improved with dithering. This is a very small amount of random noise (for example, white noise) that is added to the input before conversion. Its action is to randomize the state of LSB according to the signal. Instead of simply turning off the signal completely at low levels, it extends the effective range of signals that the ADC can convert at the expense of a slight increase in noise. Note that dithering can only increase the resolution of a sampler. It cannot improve linearity and, therefore, accuracy does not necessarily improve. An ADC load-balances servers and accelerates applications. As technology has evolved, new ADC offerings have extended features that outperform traditional load balancers and first-generation ADCs, such as Secure Sockets Layer (SSL) offloading, throughput shaping, or web application firewalls. An ADC essentially acts as a load balancer, optimizing performance, reliability, data center resource utilization, and enterprise application security. However, ADCs also perform other functions such as application acceleration, caching, compression, traffic shaping, content switching, multiplexing, and application security. Full form of ADC: Here we will learn what ADC stands for? ADC – short for „analog-to-digital converter“ in computer acronyms/abbreviations, etc. Submitted by Anushree Goswami on 19. March 2020 An analog-to-digital converter converts a continuous analog signal in time and amplitude into a digital signal that is discrete in time and amplitude.
The analog input of a converter consists of a voltage that varies between a theoretically infinite number of values. Examples include sine waves, waveforms that represent human speech, and signals from a conventional television camera. where M is the resolution of the CAN in bits and EFSR is the full-scale voltage range (also known as the „span“). EFSR is given by quantification errors is introduced by the quantification inherent in an ideal ADC. This is a rounding error between the analog input voltage of the ADC and the digitized output value. The error is non-linear and signal dependent. In an ideal ADC, where the quantization error is evenly distributed between −1/2 LSB and +1/2 LSB and the signal has a uniform distribution covering all levels of quantization, the signal-to-quantization noise ratio (SQNR) is given by The speed of a CAN varies depending on the type. The Wilkinson ADC is limited by the clock frequency that can be processed by current digital circuits.
In a successive proximity ADC, the conversion time changes with the logarithm of the resolution, which is the number of bits. Flash ADCs are certainly the fastest type of the three; The conversion is essentially done in one parallel step. Clock jitter is caused by phase noise.   ADC resolution with a scanning bandwidth between 1 MHz and 1 GHz is limited by jitter.  For low-bandwidth conversions, for example: When sampling audio signals at 44.1 kHz, clock jitter has less impact on performance.  Converter resolution indicates the number of different, i.e. discrete, values it can produce over the permissible range of analog input values. Thus, a certain resolution determines the magnitude of the quantization error and thus the maximum possible signal-to-noise ratio for an ideal ADC without the use of oversampling. Input samples are usually stored electronically in binary form in the ADC, so the resolution is usually expressed in audio bit depth.
Therefore, the number of discrete values available is usually a power of two. For example, a ADC with 8-bit resolution can encode an analog input for a different level on 256 (28 = 256). Depending on the application, values can range from 0 to 255 (that is, as unsigned integers) or from −128 to 127 (that is, as a signed integer). A digital-to-analog converter (DAC) performs the opposite function; It converts a digital signal into an analog signal. An ADC has several points of failure. Quantization errors and (assuming that ADC should be linear) nonlinearity are inherent in any analog-to-digital conversion. These errors are measured in a unit called LSB (Least Significant Bit). In the above example of an eight-bit ADC, an error of an LSB is 1/256 of the total signal range, or about 0.4%. A time-nested ADC uses parallel M CANS, where each ADC samples the data in each M:th cycle of the effective sampling clock. The result is that the sampling rate M is several times higher than what each individual ADC can handle. In practice, individual differences between ADCs affect overall performance and reduce interference-free dynamic range (SFDR).  However, there are techniques to correct these temporal nesting errors.
 There are several ADC architectures. Due to the complexity and need for precisely matched components, all but the most specialized ADCs are implemented as integrated circuits (ICs). These typically take the form of mixed-signal metal oxide (MOS) integrated circuit chips that integrate both analog and digital circuits. The quantization distortion in a very low-level audio signal relative to the bit depth of the ADC correlates with the distorted and unpleasant signal and sounds. Dithering converts distortion into noise. The undistorted signal can be accurately restored by averaging over time. Dithering is also used in the integration of systems such as electricity meters. Because the values are summed, dithering provides more accurate results than the LSB of the analog-to-digital converter.
With TCP multiplexing, ADCs compress the number of TCP sessions to save network bandwidth and send multiple signals simultaneously. Multiplexing is important because on application servers, device load and Exchange traffic increase exponentially with new sessions. Most ADCs also support integration with existing network and dynamic routing protocols such as Open Shortest Path First (OSPF), Border Gateway Protocol (BGP), Virtual Extensible LAN (VXLAN), or new Software-Defined Networking (SDN) protocols.