@article{MAKHILLJEAS201813215433,
    title = {ADC Testing Algorithm for ENOB by Wavelet Transform using
LabView Measurements and MATLAB Simulations},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {13},
    number = {2},
    pages = {398-405},
    year = {2018},
    issn = {1816-949x},
    doi = {jeasci.2018.398.405},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2018.398.405},
    author = {Emad A. and},
    keywords = {Effective Number of Bits (ENOB),Discrete Wavelet Transforms (DWT),Analog-to-Digital Converters (ADCs),components,multi-resolutions,evaluating},
    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 (ADC’s) 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 ADC’s output signal and is extremely sensitive to
noise. This makes ENOB estimation process longer and complex as the ADC’s resolutions increases. In this
research of evaluating non-ideal ADC’s (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 ADC’s parameters.}
    }