Chung-Shin J. Chen

Learn More
We present methods for velocity estimation from discrete and quantized position samples using adaptive windowing. Previous methods necessitate tradeoffs between noise reduction, control delay, estimate accuracy, reliability, computational load, transient preservation, and difficulties with tuning. In contrast, a first-order adaptive windowing method is(More)
In this paper, we present new methods for velocity estimation from discrete 1 and quantized position samples. The proposed methods are based on adaptive windowing and address the shortcomings of the previous methods which necessitate tradeoos between noise reduction, control delay, estimate accuracy, reliability, computational load, transient preservation,(More)
A method is described to estimate velocity from discrete and quantized position samples via adaptive windowing. It addresses the shortcomings of previously known methods which necessitate tradeo s between noise reduction, control delay, estimate accuracy, reliability, computational load, transient preservation, and which cause di culties with tuning. The(More)
  • 1