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FindGraph: Filter data to eliminate noise at high frequencies

Introduction
->> FindGraph
->> Features
->> System Requirements
   
Quick Start Tutorial
->> Data
->> Import/Export
->> Digitize Data
->> Transfrom Data
->> Procrustes Analysis
->> Filter Data
->> Convolution
->> Interpolation
->> Linear Regression
->> Curve Fitting
->> Famous Curves
->> Formula
->> Background
->> Editor
->> Occupation
->> Distribution
->> Diagram
->> Analysis
->> Distances
->> Statistics
->> Options
->> Аctive Document
->> Fiting Automation
   
Menus
->> File
->> Edit
->> View
->> Data
->> Plot
->> Fit
->> Analysis
->> Graphing
->> List
->> Help
->> Status Bar
   
Advanced Options
->> Import Points
->> Digitize
->> Export Ponts
->> Save as Picture
->> Approximation
->> Fit Peaks
->> Parametric Graph
->> Transform Points
->> Editor
->> Commentary
->> Statistics
->> Zoom
->> Automation
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Filter Data

Select menu item <Analysis><Filter> to apply the Fast Fourier Transform (FFT) filters or the Daubechies D4 Wavelet Tranform for digitally filtering data.

FindGraph provides five filters for digitally filtering data:

  • The low pass filter allows you to eliminate noise at high frequencies.
  • The high pass filter to eliminate noise at low frequencies.
  • The band pass filter allows you to eliminate noise above and below a specified frequency range.
  • The band block filter allows you to eliminate noise within a specified frequency range.
  • The threshold filter allows you to eliminate noise corresponding to frequency components that are below a specified threshold.
  • In dialog you can modify low and high frequencies and amplitude threshold level.

An inverse FFT and Wavelet Transform is performed on the filtered frequency spectrum to yield a new data series containing the original data with the noise removed.

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