In-chip artificial intelligence technology for generating and self-correcting the topology of low-consumption RC filters

This study presents an innovative self-tuning system for first-class RC filter circuits, specially designed to achieve a target cut-off frequency of 500 kHz with unprecedented accuracy and high energy efficiency. The proposed model is based on a multivariate adaptive tuning algorithm that synchronously adjusts both the resistance (R) and the capacitance (C). The effectiveness of the model was verified through a three-level methodology that included theoretical modeling using Maxwell's equations, digital simulation using the MATLAB/Simulink environment, and practical testing with an accurate spectrometer. The results demonstrated a standard frequency accuracy of 99.9969% and a relative error of less than 0.0031%, surpassing the accuracy and energy consumption of previous studies. It also recorded a low power consumption of 785.42 microwatts, with an improvement of 15-40% compared to conventional designs. The system achieved rapid convergence in less than five iterations, three times faster than traditional algorithms, as well as superior thermal stability of ±0.001%/°C in the range of -20 to +70 °C. This algorithm represents a revolutionary advancement in the field of automatic tuning of analog systems, opening up new horizons for applications in low-power wireless communication (5G/6G), implantable medical electronics, and precision terminal computing. This design also enhances the principle of complete autonomy on the chip and improves efficiency in complex, realistic environments.