Category Archives: Fundamental

signal smooth filtering (include moving average algorithm)

import numpy def smooth(x,window_len=5,window=’hanning’): “””smooth the data using a window with requested size. This method is based on the convolution of a scaled window with the signal. The signal is prepared by introducing reflected copies of the signal (with the … Continue reading

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Savitzky Golay Filtering . py

A useful filter for signal smoothing def savitzky_golay(y, window_size, order, deriv=0, rate=1): r”””Smooth (and optionally differentiate) data with a Savitzky-Golay filter. The Savitzky-Golay filter removes high frequency noise from data. It has the advantage of preserving the original shape and … Continue reading

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Signal Smoothing

Source: Signal Smoothing Algorithms   Theory The signal-to-noise ratio (SNR) of a signal can be enhanced by either hardware or software techniques. The wide use of personal computers in chemical instrumentation and their inherent programming flexibility make software signal … Continue reading

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Langmuir’s Equation for Evaporation

Irving Langmuir (1881 Jan 13 – 1957 Aug 16) once derived a neat equation that describes the evaporation of a liquid. And he used an astonishingly elegant argument to get it. We begin to follow Langmuir’s logical path by assuming … Continue reading

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