Chung-Shin J. Chen

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—We present methods for velocity estimation from discrete and quantized position samples using adaptive windowing. first-order adaptive windowing method is shown to be optimal in the sense that it minimizes the velocity error variance while maximizes the accuracy of the estimates, requiring no tradeoff. Variants of this method are also discussed. The(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 tradeoos between noise reduction, control delay, estimate accuracy, reliability, computational load, transient preservation, and which cause diiculties with tuning. The(More)
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