Abstract: In this study, a new time frequency domain approach (well known as Wavelet Transform) will be applied to measure and analyze Analog-to-Digital Converters (ADCs) Effective Number of Bits (ENOB). In classical testing, ENOB is based on the Ratio of the Signal to Noise components (SNR) whose coefficients are driven via frequency domain that is fourier transform of the ADCs output signal and is extremely sensitive to noise. This makes ENOB estimation process longer and complex as the ADCs resolutions increases. In this research of evaluating non-ideal ADCs (real time testing), a new proposed evaluation method based on wavelet transform was used to estimate the worst case ENOB through the output signal dynamic range. Comparing with the classical testing methods, wavelet transform have shortened testing time and reduced computations complexity due to its special properties of multi-resolutions analysis. In addition, wavelet transform have improved ENOB estimation since, noise averaging is not part of testing algorithms. This method of wavelet transform improves the DSP testing for ADCs parameters.
Emad A. Awada and Cajetan M. Akujuobi, 2018. ADC Testing Algorithm for ENOB by Wavelet Transform using LabView Measurements and MATLAB Simulations. Journal of Engineering and Applied Sciences, 13: 398-405.