Nonlinearity in the transfer function of analog-to-digital converters (ADCs) is a major factor contributing to measurement errors in digital signal processing systems. While ideal ADCs produce a linear mapping between input voltage and digital output code, real devices introduce deviations that distort the spectral composition of the signal. Manufacturers typically specify only integral (INL) and differential (DNL) nonlinearity parameters, which provide limited insight into the practical impact of these imperfections.

This study presents a modeling approach for estimating the influence of ADC nonlinearity on the amplitude characteristics of digital signal spectra. Based on known values of INL and DNL, analytical relationships are used to simulate the appearance of additional harmonics and the deviation of the fundamental spectral component, without requiring experimental reconstruction of the actual ADC transfer function. Both sinusoidal and polyharmonic input signals are considered to reflect realistic measurement conditions.

Simulation results show that even moderate nonlinearity levels can lead to measurable spectral distortion, which may compromise signal integrity in precision applications. The developed approach provides a practical framework for evaluating the suitability of ADCs in spectral measurement systems and helps anticipate performance limitations before hardware implementation.

The findings can support engineers and designers in optimizing ADC selection and mitigating error sources in digital measurement devices, particularly in fields requiring high spectral accuracy, such as instrumentation, communications, and signal diagnostics.