Importance sampling for detection systems with a memoryless non-linearity

The authors present an importance sampling technique designed for a detection system that contains a memoryless nonlinearity followed by a linear filter. Examples are included that are indicative of the effort involved and the improvement that can be expected when using the proposed technique. Numerical results show the technique provides a significant improvement over standard Monte Carlo simulation and an improvement over conventional importance sampling that increases with the memory length of the system