Package likelihoodDetectionModule.normalizer

Class SplitWindowNorm

java.lang.Object
likelihoodDetectionModule.normalizer.SplitWindowNorm
All Implemented Interfaces:
Normalizer
public class SplitWindowNorm extends Object implements Normalizer
A Split Window normalizer implementation. Basically there is a wide and narrow blockAverager. The signal estimate is the output of the narrow average, divided by the width of the narrow block. The noise estimate is the output of the wide average, minus the signal (output of the narrow average). The noise is then divided by the difference of the two widths (wide width - narrow width). A list of blockTimeStamp objects is kept as data comes in since the blockAverage modules will cause lags in the processing and might not produce output immediately. When data is produces, the oldest blockTimeStamp object is used to create a block the same size as the input data, therefore data will come out in same sized and timestamped blocks as they came in
Author:
dave