Converting analog to digital creates approximation errors due to quantization noise. Here’s how to minimize the impact.
Analog to Digital Converters (ADCs) are critical components in high-speed, high-resolution applications where an analog or RF signal has to be processed, stored, or transported in digital form. ADC performance requirements vary by application and include resolution, dynamic range, linearity, power consumption, speed, bandwidth, SNDR (Signal-to-Noise and Distortion Ratio), and ENOB (Effective Number of Bits).
Designers face a wide variety of challenges in verifying ADC functionality against performance specifications. Converting a continuous analog signal into a discrete digital code yields unavoidable approximation errors due to quantization noise, which designers can minimize by choosing the most appropriate architecture for their application. In nanometer technology nodes, ADC performance is also significantly impacted by device noise, postlayout parasitics, process variability, and device mismatch.
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