Optimal Sizing of Recycling Folded Cascode Amplifier for Low-Frequency Applications Using New Hybrid Swarm Intelligence-Based Technique

A new efficient design approach for sizing a high-performance analog amplifier circuit namely the recycling folded cascode (RFC) amplifier is presented. An RFC amplifier is an enhanced version of the conventional folded cascode amplifier and achieves better slew rate, gain, bandwidth, offset, etc. for same area and power budget. Low-frequency amplifiers such as biomedical or neural have a demanding requirement of low area, low power, and low noise apart from meeting other optimal design specifications which have inherent trade-off among themselves. As a result, manual sizing becomes a computationally inefficient approach. Thus, swarm-based optimization techniques have been employed to efficiently determine the optimal sizing for the RFC amplifier such that the area is minimized while meeting all the optimal design specifications considering the constraints. A new hybrid whale particle swarm optimization (HWPSO) algorithm is employed which takes advantage of the good qualities of both the whale algorithm and the PSO algorithm to optimize the area with less computational complexity. Simulations and statistical analysis have been performed and comparisons with other state of art algorithms reveals that HWPSO-based approach achieves a minimum circuit area of 21 µm2 with a mean Friedman’s statistical rank of 2.05 while meeting optimal design specifications for low-frequency systems. Finally, validation with circuit design tool Cadence Virtuoso is done and pre- as well as postlayout analysis have been performed which further illustrated a close agreement with algorithmic results.