A novel digital adaptive blind calibration technique for frequency-interleaved analog-to-digital converters (FI-ADCs) with arbitrary numbers of channels is proposed. It performs the estimation and correction of multiple inherent circuit deficiencies alternately and recursively in the background, including spectral leakage, harmonic folding, jitter, I/Q mirror and aliasing images, and suffices to deliver projected calibration capabilities with deliberately chosen initial guesses. We are of the opinion that this is the first study to address the joint channel identification and error compensation problem encountered in the FI-ADC design. For the efficient implementation, an analytical time-interleaving-like equivalent model is formulated such that the number of unknown mismatch parameters is significantly reduced, and signals devoted to cyclic estimation are maximally decimated. This derived model not only propounds a better perspective for comprehension and interpretation of the FI system mechanism but also enables sufficient scalability and flexibility of the developed calibration framework. Extensive simulation results further show that this novel architecture achieves a good balance between the computational complexity and convergence, and provides an exceptional and relatively flat effective number of bit (ENOB) performance over a wide bandwidth.