  A digital finite impulse response (FIR) filter design is fully synthesizable,
thanks to the mature CAD support of digital circuitry. On the contrary, analog
mixed-signal (AMS) filter design is mostly a manual process, including
architecture selection, schematic design, and layout. This work presents a
systematic design methodology to automate AMS FIR filter design using a time
approximation architecture without any tunable passive component, such as
switched capacitor or resistor. It not only enhances the flexibility of the
filter but also facilitates design automation with reduced analog complexity.
The proposed design flow features a hybrid approximation scheme that
automatically optimize the filter's impulse response in light of time
quantization effects, which shows significant performance improvement with
minimum designer's efforts in the loop. Additionally, a layout-aware regression
model based on an artificial neural network (ANN), in combination with
gradient-based search algorithm, is used to automate and expedite the filter
design. With the proposed framework, we demonstrate rapid synthesis of AMS FIR
filters in 65nm process from specification to layout.
