Circuit Parameter

Circuit parameter optimization aims to find the ideal settings for electronic components to maximize performance and efficiency in various applications, from neural networks to power converters. Current research heavily utilizes machine learning techniques, including neural networks, random forests, and genetic algorithms, often coupled with simulation tools like SPICE, to automate and accelerate the optimization process, addressing challenges like high dimensionality and conflicting objectives. These advancements significantly reduce design time and improve the performance of diverse circuits, impacting fields ranging from robotics (through improved tactile sensing) to energy-efficient electronics.