我想问你关于用java编写的任何经验模式分解库。我找不到任何东西。最好是开源的。
谢谢
问问题
1527 次
1 回答
1
我刚刚找到了一个 C 实现（https://code.google.com/p/realtime-emd/）并将其翻译成 Java。所以请注意，这段代码不是Java风格的代码，它只是编译和运行的Java代码。
/*
* To change this template, choose Tools | Templates
* and open the template in the editor.
*/
package tryout.emd;
/**
*
* @author Krusty
*/
public class Emd {
private void emdSetup(EmdData emd, int order, int iterations, int locality) {
emd.iterations = iterations;
emd.order = order;
emd.locality = locality;
emd.size = 0;
emd.imfs = null;
emd.residue = null;
emd.minPoints = null;
emd.maxPoints = null;
emd.min = null;
emd.max = null;
}
private void emdResize(EmdData emd, int size) {
int i;
// emdClear(emd);
emd.size = size;
emd.imfs = new double[emd.order][]; // cnew(double*, emd->order);
for(i = 0; i < emd.order; i++) emd.imfs[i] = new double[size]; // cnew(double, size);
emd.residue = new double[size]; // cnew(double, size);
emd.minPoints = new int[size / 2]; // cnew(int, size / 2);
emd.maxPoints = new int[size/2]; //cnew(int, size / 2);
emd.min = new double[size]; // cnew(double, size);
emd.max = new double[size]; // cnew(double, size);
}
private void emdCreate(EmdData emd, int size, int order, int iterations, int locality) {
emdSetup(emd, order, iterations, locality);
emdResize(emd, size);
}
private void emdDecompose(EmdData emd, double[] signal) {
int i, j;
System.arraycopy(signal, 0, emd.imfs[0], 0, emd.size); // memcpy(emd->imfs[0], signal, emd->size * sizeof(double));
System.arraycopy(signal, 0, emd.residue, 0, emd.size); // memcpy(emd->residue, signal, emd->size * sizeof(double));
for(i = 0; i < emd.order - 1; i++) {
double[] curImf = emd.imfs[i]; // double* curImf = emd->imfs[i];
for(j = 0; j < emd.iterations; j++) {
emdMakeExtrema(emd, curImf);
if(emd.minSize < 4 || emd.maxSize < 4) break; // can't fit splines
emdInterpolate(emd, curImf, emd.min, emd.minPoints, emd.minSize);
emdInterpolate(emd, curImf, emd.max, emd.maxPoints, emd.maxSize);
emdUpdateImf(emd, curImf);
}
emdMakeResidue(emd, curImf);
System.arraycopy(emd.residue, 0, emd.imfs[i+1], 0, emd.size); // memcpy(emd->imfs[i + 1], emd->residue, emd->size * sizeof(double));
}
}
// Currently, extrema within (locality) of the boundaries are not allowed.
// A better algorithm might be to collect all the extrema, and then assume
// that extrema near the boundaries are valid, working toward the center.
private void emdMakeExtrema(EmdData emd, double[] curImf) {
int i, lastMin = 0, lastMax = 0;
emd.minSize = 0;
emd.maxSize = 0;
for(i = 1; i < emd.size - 1; i++) {
if(curImf[i - 1] < curImf[i]) {
if(curImf[i] > curImf[i + 1] && (i - lastMax) > emd.locality) {
emd.maxPoints[emd.maxSize++] = i;
lastMax = i;
}
} else {
if(curImf[i] < curImf[i + 1] && (i - lastMin) > emd.locality) {
emd.minPoints[emd.minSize++] = i;
lastMin = i;
}
}
}
}
private void emdInterpolate(EmdData emd, double[] in, double[] out, int[] points, int pointsSize) {
int size = emd.size;
int i, j, i0, i1, i2, i3, start, end;
double a0, a1, a2, a3;
double y0, y1, y2, y3, muScale, mu;
for(i = -1; i < pointsSize; i++) {
i0 = points[mirrorIndex(i - 1, pointsSize)];
i1 = points[mirrorIndex(i, pointsSize)];
i2 = points[mirrorIndex(i + 1, pointsSize)];
i3 = points[mirrorIndex(i + 2, pointsSize)];
y0 = in[i0];
y1 = in[i1];
y2 = in[i2];
y3 = in[i3];
a0 = y3 - y2 - y0 + y1;
a1 = y0 - y1 - a0;
a2 = y2 - y0;
a3 = y1;
// left boundary
if(i == -1) {
start = 0;
i1 = -i1;
} else
start = i1;
// right boundary
if(i == pointsSize - 1) {
end = size;
i2 = size + size - i2;
} else
end = i2;
muScale = 1.f / (i2 - i1);
for(j = start; j < end; j++) {
mu = (j - i1) * muScale;
out[j] = ((a0 * mu + a1) * mu + a2) * mu + a3;
}
}
}
private void emdUpdateImf(EmdData emd, double[] imf) {
int i;
for(i = 0; i < emd.size; i++)
imf[i] -= (emd.min[i] + emd.max[i]) * .5f;
}
private void emdMakeResidue(EmdData emd, double[] cur) {
int i;
for(i = 0; i < emd.size; i++)
emd.residue[i] -= cur[i];
}
private int mirrorIndex(int i, int size) {
if(i < size) {
if(i < 0)
return -i - 1;
return i;
}
return (size - 1) + (size - i);
}
public static void main(String[] args) {
/*
This code implements empirical mode decomposition in C.
Required paramters include:
- order: the number of IMFs to return
- iterations: the number of iterations per IMF
- locality: in samples, the nearest two extrema may be
If it is not specified, there is no limit (locality = 0).
Typical use consists of calling emdCreate(), followed by
emdDecompose(), and then using the struct's "imfs" field
to retrieve the data. Call emdClear() to deallocate memory
inside the struct.
*/
double[] data = new double[]{229.49,231.94,232.97,234,233.36,235.15,235.64,235.78,238.95,242.09,240.61,240.29,237.88,252.11,259.16,263.4,262.1,254.85,254.42,261.27,253.92,259.04,251.58,248.96,239.49,229.39,247.02,249.48,254.9,251.27,246.85,245.43,241.52,231.23,235.67,239.99,238.49,237.41,246.4,249.83,253.67,256.71,255.9,248.93,244.05,242.49,236.52,243.63,246.55,247.3,252.56,259.91,264.41,266.55,262.75,266.33,263.53,261.62,259.38,260.94,249.14,244.63,241.66,240.16,241.81,251.57,251.01,252.49,250.23,244.89,245.79,244.55,243.04,238.84,244.98,247.26,251.91,252.81,252.16,256.83,253.8,251.03,250.19,254.66,254.74,255.76,254.52,252.95,254.57,252.29,243.32,244.88,242.26,240.84,245.05,246.12,243.02,242.79,239.05,233.34,236.22,233.69,234.99,235.84,236.43,243.46,245.25,251.67,250.73,255.7,255.85,256.18,259.71,260.7,262.8,268.98,267.81,275.46,275.98,279.85,280.99,284.3,283.17,278.99,279.48,275.96,274.77,270.99,281.01,281.25,281.28,286,287.25,290.35,291.9,294.01,306.1,309.27,301,302.01,301.02,299.03,300.36,299.59,299.38,296.86,292.72,295.83,300.87,304.21,309.53,308.43,309.87,307.4,309.3,307.96,299.58,298.61,293.31,292.25,299.96,298.31,304.76,300.26,306.16,306.35,308.17,302.61,307.72,309.42,308.73,311.36,309.48,312.2,310.98,311.76,312.84,311.5,311.57,312.43,311.81,313.37,315.3,316.24,314.72,315.77,316.54,316.36,314.78,313.71,320.52,322.2,324.83,324.57,326.89,333.05,332.26,334.97,336.19,338.92,331.3,329.54,323.55,317.75,328.19,332.03,334.41,333.79,326.88,330.01,335.56,334.87,334.01,336.99,342.22,345.45,348.33,344.81,347.06,349.32,350.02,353.16,348.47,340.94,329.32,333.22,333.47,338.6,343.52,339.72,342.46,349.69,350.12,345.61,346,342.8,337.15,342.33,343.86,335.95,320.95,325.46,321.59,329.99,331.84,329.88,335.5,341.89,340.82,341.33,339.06,338.94,335.1,331.83,329.59,328.76,328.8,325.86,321.72,323.28,326.9,323.3,318.47,322.74,328.59,333.01,341.07,343.32,340.8,340.54,337.23,340.52,336.78,338.64,339.98,337.23,337.15,338.06,339.86,337.7,337.06,331.15,324.15,326.91,330.54,331.18,326.02,325.22,323.07,327.54,325.81,328.15,338.28,336.03,336.6,334.01,328.76,322.93,323.12,322.39,316.96,317.64,323.32,317.78,316.24,311.47,306.67,316.37,313.76,322.14,317.39,322.93,326.06,324.87,326.46,333.84,339.84,342.11,347.4,349.84,344.28,344.04,348.19,347.95,354.9,363.54,366.51,376.28,376.66,382.51,387.56,392.34,381.81,381.07,379.76,385.86,378.24,381.8,367.01,363.37,343.52,363.74,353.71,363.44,366.64,372.89,370.04,370,356,346.26,346.66,363.35,365.85,363.46,373.05,379.27,379.29,374.27,370.57,363.78,369.32,373.39,373.6,367.12,369.51,374.06,378.61,382.17,389.51,400.33,402.1,400.83,390.79,393.2,392.1,388.3,386.11,379.85,370.85,364.32,362.28,367.87,367.01,359.65,378.14,389.3,391.15,397.22,410.42,408.46,410.65,387.68,384.46,382.09,394.63,386.85,389.6,393.58,393.84,393.67,385.63,386.5,392.01,389.25,388.76,395.08,384.43,374.65,374.06,368.85,378.16,374.21,367.05,364.65,358.88,366.18,356.92,353.59,365.8,362.96,371.71,377.28,379,382.22,380.22,378.41,379.94,382.82,381.09,378.14,369.75,368.54,370.56,371.72,385.08,385.57,387.61,392.26,395.37,391.59,394,393.88,399.94,402.09,406.56,410.81,410.15,411.62,410.95,409.82,408.29,413.04,417.33,416.01,408.76,415.68,408.87,434.4,432.43,435,440.58,443.95,443.67,442.63,447.06,451.24,455.96,463.6,479.63,479.88,488.81,495.48,484.01,488.43,488.34,500.72,498.96,502.22,508.07,511.33,520.71,527.55,529.53,530.22,518.53,515.71,516.12,527.11,530.21,536.85,552.51,573.4,569.49,569.5,584.6,589.33,585.96,582.89,579.69,590.32,597.61,600.67,593.12,583.09,601.65,612.05,607.17,616.29,618.77,611.19,609.01,605.68,588.62,564.21,592.97,591.64,571.32,557.25,556.01,544.9,593.26,591.02,586.45,567.95,566.15,569.9,565.85,549.74,553.85,552.59,553.56,554.86,551.16,542.9,537.99,531.09,515.57,515.82,545.87,541.68,554.9,549.8,546.86,556.56,563.27,561.87,545.59,548.8,547.38,555.78,556.03,564.39,555.49,560.35,556.46,555.84,558.37,569.7,571.29,569.66,561.81,566.12,555.1,556.33,558.73,553.43,567.97,576.26,582.96,593.2,589.25,597.04,591.52,587.84,582.46,588.37,590.25,590.28,589.62,597.46,587.71,587.26,584.43,559.19,559.1,569.1};
Emd emd = new Emd();
EmdData emdData = new EmdData();
int order = 4;
emd.emdCreate(emdData, data.length, order, 20, 0);
emd.emdDecompose(emdData, data);
for (int i=0;i<data.length;i++) {
System.out.print(data[i]+";");
for (int j=0;j<order; j++) System.out.print(emdData.imfs[j][i] + ";");
System.out.println();
}
}
private static class EmdData {
protected int iterations, order, locality;
protected int[] minPoints, maxPoints;
protected double[] min, max, residue;
protected double[][] imfs;
protected int size, minSize, maxSize;
}
}
于 2013-12-30T20:43:17.607 回答