Use Multilayer Perceptron in Calibrating Multistage Non-linearity of Split Pipelined-ADC

Abstract

A split-based background calibration technique for pipelined-ADC is proposed in this brief to handle both capacitors' mismatches and non-linearity of residue amplifiers in multiple pipeline stages. Some concepts and approaches of machine learning, say multilayer perceptron and backpropagation algorithm, are introduced to deal with the problems appearing in modeling and solving the nonlinear calibration filter. Computer simulations demonstrate an exaltation of both SNDR and SFDR for more than 50dB in a 15-bit 7-stages pipelined-ADC with non-ideal first three stages.