In this paper, we characterize and evaluate the effectiveness of a pseudo-random-based implicit functional testing technique for analog and mixed-signal circuits. The analog test problem is transformed into the digital domain by embedding the device-under-test (DUT) between a digital-to-analog-converter and an analog-to-digital converter. The pseudo-random testing technique uses band-limited digital white noise (pseudo-random-patterns) as input stimulus. The signature is constructed by computing the cross-correlation between the digitized output response and the pseudo-random input sequence. We have implemented a DSP-based hardware testbed to evaluate the effectiveness of the pseudo-random testing technique. Our test results show that we can achieve close to 100% yield and fault coverage by carefully selecting only two cross-correlation samples. Noise level and total harmonic distortion below 0.1% and 0.5%, respectively, do not affect the classification accuracy.