Discarding outliers using a nonlinear resistive network

The authors describe an algorithm for discarding outliers in noisy and possibly sparse sensor data. The authors demonstrate a network that incorporates robustness in its computation and the network settles to its final solution in a few time constants. The work is a modification of a resistive network which provides for detection and removal of outliers in image segmentation. A nonlinear resistive network is used to isolate an input point from the rest of the network when the input point differs significantly from the neighborhood average. The resistive network outlier algorithm has a simple elegant embodiment in analog real-time VLSI hardware. The authors demonstrate the algorithm with simulations on a laser radar image