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Kernel Based Filter · psambit9791/jdsp Wiki · GitHub
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Kernel Based Filter
Sambit Paul edited this page Dec 2, 2023
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- Median Filter
- Savitzky–Golay Filter
- Wiener Filter
This page explains the usage of all these filters in the context of this library.
The parameters for this filter are as follows:
- Window Size ⇨ 7
int windowSize = 7; //can be anything less than length of signal
MedianFilter mf = new MedianFilter(signal, windowSize); //signal is of type double[]
double[] out = mf.filter(); //get the result after filtering
The parameters for this filter are as follows:
- Mode ⇨ [pad | signal | pad]
- "mirror": 4 3 2 | 1 2 3 4 5 6 7 8 | 7 6 5
- "constant": 0 0 0 | 1 2 3 4 5 6 7 8 | 0 0 0
- "nearest": 1 1 1 | 1 2 3 4 5 6 7 8 | 8 8 8
- "wrap": 6 7 8 | 1 2 3 4 5 6 7 8 | 1 2 3
- Window Size ⇨ 7
- Polynomial Order ⇨ 2
- Derivative ⇨ 0
- Delta ⇨ 1
String mode = "mirror" //can be any of the operating modes described above
int windowSize = 5; //can be anything less than length of signal
int polyOrder = 2; //Order of the polynomial used to generate coefficients
int deriv = 0; // Order of derivative
int delta = 1; // Spacing of samples to which filter is applied
Savgol s1 = new Savgol(signal, windowSize, polyOrder, deriv, delta); //signal is of type double[]
// ALSO: Savgol s1 = new Savgol(signal, windowSize, polyOrder) set deriv=0, delta=1 by DEFAULT
double[] out = s1.filter(mode); //get the result after filtering
The parameters for this filter are as follows:
- Window Size ⇨ 7
int windowSize = 7; //can be anything less than length of signal
Wiener wf = new Wiener(signal, windowSize); //signal is of type double[]
double[] out = wf.filter(); //get the result after filtering
Wiki
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Filters
- IIR Filters
- FIR Filters
- Kernel-Based Filter
- Adaptive Filters
-
Signals
-
Peak Detection
-
Transformations
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Speech
-
Windowing
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