"Sampling Theory for Embedded Systems: From Nyquist and Aliasing to Reliable ADC Acquisition" Sampling an analog signal seems straightforward: connect the signal to an analog-to-digital converter, configure a sampling frequency, read conversion results, and process the numbers in firmware. In practice, ADC acquisition is one of the most common sources of subtle measurement errors in embedded systems. An ADC can report valid numerical values while misrepresenting the physical signal being measured. A high-frequency disturbance can appear as a low-frequency oscillation. A fast transient can occur between samples and disappear. A slowly varying sensor signal can become noisy because the ADC input capacitor never settles. Increasing the sampling rate may solve one issue while creating another involving CPU load, DMA bandwidth, memory usage, or analog front-end limitations. Reliable digital measurements require the signal bandwidth, analog filtering, sampling clock, ADC acquisition behavior, and firmware processing to be designed as one coordinated system. Nyquist theory defines the mathematical limits. Anti-alias filters help satisfy those limits physically. The ADC must acquire the voltage accurately. Firmware must preserve timing and sample integrity. Verification must prove that the digital values represent the real-world signal.