Fast estimation of interconnects delay in RLC trees using neural network

This paper presents a novel approach based on training an artificial neural network to estimate interconnects delay in RLC trees. The neural network can be described as the mapping of a set of inputs (damping factor and input signal rise time) to the corresponding output (propagation delay) through a system of weighting factors and biases. In this work, we employ an exponential signal as the input signal. Using the proposed method, we would compute efficiently and accurately the propagation delay time of RLC trees.