Abstract: Noise is the extraneous information that changes the original signal information. It is not possible to completely suppress the noise, but we can reduce it. Signal to noise ratio is very important in studies based on signal. It is a measure of the signal level in the measured waveform. The noise affecting the signal is random in nature. The average value of the random noise affected on a signal at different time instants is zero. Ensemble averaging is one of the best noise filtering methods and is based on the concept of noise random nature. In ensemble average successive sets of collected data are summed point by point. Therefore, a prerequisite for the application of ensemble averaging method is the ability to reproduce the signal many times starting always from the same data point. Signal to noise ratio can be improved in proportion to the square root of the number of repetition of the signal. As the number of repetition increases, the signal to noise ratio also increases. Ensemble averaging filtering can be applied to a number of applications like spectroscopy and non-destructive testing.

Keywords: Ensemble Averaging, FPGA, noise reduction, average filter, noise filter.