Locally monotonic regression
A novel technique for shaping/smoothing discrete signals is introduced. The approach, known as locally monotonic regression, entails finding a locally monotonic signal that best approximates the given signal. The authors present the problem within a theoretical framework, show the existence of a solution, and give an algorithm that computes it. Several examples are used to illustrate the approach.<<ETX>>