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
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
Signal Smoothing
Source: http://www.chem.uoa.gr/applets/appletsmooth/appl_smooth2.html 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
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