Sensitivity-Informed Bayesian Inference for Home PLC Network Models with Unknown Parameters
Bayesian inference is used to calibrate a bottom-up home PLC network model with unknown loads and wires at frequencies up to 30 MHz.A network topology with over 50 parameters is calibrated using global sensitivity analysis and transitional Markov Chain Monte Carlo (TMCMC).The sensitivity-informed Bayesian inference computes Sobol indices for each n