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public static double[] filter(double[] b, double[] a, double[] x) {
double[] filter = null;
double[] a1 = getRealArrayScalarDiv(a,a[0]);
double[] b1 = getRealArrayScalarDiv(b,a[0]);
int sx = x.length;
filter = new double[sx];
filter[0] = b1[0]*x[0];
for (int i = 1; i < sx; i++) {
filter[i] = 0.0;
for (int j = 0; j <= i; j++) {
int k = i-j;
if (j > 0) {
if ((k < b1.length) && (j < x.length)) {
filter[i] += b1[k]*x[j];
}
if ((k < filter.length) && (j < a1.length)) {
filter[i] -= a1[j]*filter[k];
}
} else {
if ((k < b1.length) && (j < x.length)) {
filter[i] += (b1[k]*x[j]);
}
}
}
}
return filter;
}
转化率
public static double[] conv(double[] a, double[] b) {
double[] c = null;
int na = a.length;
int nb = b.length;
if (na > nb) {
if (nb > 1) {
c = new double[na+nb-1];
for (int i = 0; i < c.length; i++) {
if (i < a.length) {
c[i] = a[i];
} else {
c[i] = 0.0;
}
}
a = c;
}
c = filter(b, new double [] {1.0} , a);
} else {
if (na > 1) {
c = new double[na+nb-1];
for (int i = 0; i < c.length; i++) {
if (i < b.length) {
c[i] = b[i];
} else {
c[i] = 0.0;
}
}
b = c;
}
c = filter(a, new double [] {1.0}, b);
}
return c;
}
反卷积
public static double[] deconv(double[] b, double[] a) {
double[] q = null;
int sb = b.length;
int sa = a.length;
if (sa > sb) {
return q;
}
double[] zeros = new double[sb - sa +1];
for (int i =1; i < zeros.length; i++){
zeros[i] = 0.0;
}
zeros[0] = 1.0;
q = filter(b,a,zeros);
return q;
}
反卷积
public static double[] deconvRes(double[] b, double[] a) {
double[] r = null;
r = getRealArraySub(b,conv(a,deconv(b,a)));
return r;
}
getRealArraySub
public static double[] getRealArraySub(double[] dSub0, double[] dSub1) {
double[] dSub = null;
if ((dSub0 == null) || (dSub1 == null)) {
throw new IllegalArgumentException("The array must be defined or diferent to null");
}
if (dSub0.length != dSub1.length) {
throw new IllegalArgumentException("Arrays must be the same size");
}
dSub = new double[dSub1.length];
for (int i = 0; i < dSub.length; i++) {
dSub[i] = dSub0[i] - dSub1[i];
}
return dSub;
}
getRealArrayScalarDiv
public static double[] getRealArrayScalarDiv(double[] dDividend, double dDivisor) {
if (dDividend == null) {
throw new IllegalArgumentException("The array must be defined or diferent to null");
}
if (dDividend.length == 0) {
throw new IllegalArgumentException("The size array must be greater than Zero");
}
double[] dQuotient = new double[dDividend.length];
for (int i = 0; i < dDividend.length; i++) {
if (!(dDivisor == 0.0)) {
dQuotient[i] = dDividend[i]/dDivisor;
} else {
if (dDividend[i] > 0.0) {
dQuotient[i] = Double.POSITIVE_INFINITY;
}
if (dDividend[i] == 0.0) {
dQuotient[i] = Double.NaN;
}
if (dDividend[i] < 0.0) {
dQuotient[i] = Double.NEGATIVE_INFINITY;
}
}
}
return dQuotient;
}
示例使用
示例使用
double[] a, b, q, u, v, w, r, z, input, outputVector;
u = new double [] {1,1,1};
v = new double [] {1, 1, 0, 0, 0, 1, 1};
w = conv(u,v);
System.out.println("w=\n"+Arrays.toString(w));
a = new double [] {1, 2, 3, 4};
b = new double [] {10, 40, 100, 160, 170, 120};
q = deconv(b,a);
System.out.println("q=\n"+Arrays.toString(q));
r = deconvRes(b,a);
System.out.println("r=\n"+Arrays.toString(r));
a = new double [] {2, -2.5, 1};
b = new double [] {0.1, 0.1};
u = new double[31];
for (int i = 1; i < u.length; i++) {
u[i] = 0.0;
}
u[0] = 1.0;
z = filter(b, a, u);
System.out.println("z=\n"+Arrays.toString(z));
a = new double [] {1.0000,-3.518576748255174,4.687508888099475,-2.809828793526308,0.641351538057564};
b = new double [] { 0.020083365564211,0,-0.040166731128422,0,0.020083365564211};
input = new double[]{1,2,3,4,5,6,7,8,9};
outputVector = filter(b, a, input);
System.out.println("outputVector=\n"+Arrays.toString(outputVector));
输出
w=
[1.0, 2.0, 2.0, 1.0, 0.0, 1.0, 2.0, 2.0, 1.0]
q=
[10.0, 20.0, 30.0]
r=
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
z=
[0.05, 0.1125, 0.115625, 0.08828125, 0.0525390625, 0.021533203124999997, 6.469726562499979E-4, -0.009957885742187502, -0.012770843505859377, -0.010984611511230471, -0.007345342636108401, -0.003689372539520266, -9.390443563461318E-4, 6.708808243274683E-4, 0.0013081232085824014, 0.0012997135985642675, 9.705803939141337E-4, 5.633686931105333E-4, 2.189206694310998E-4, -8.033509766391922E-6, -1.195022219235398E-4, -1.453610225212288E-4, -1.219501671897661E-4, -7.975719772659323E-5, -3.8721413563358476E-5, -8.523168090901481E-6, 8.706746668052387E-6, 1.5145017380516224E-5, 1.4577898391619086E-5, 1.0649864299265747E-5, 6.023381178272641E-6]
outputVector=
[0.020083365564211, 0.11083159422936348, 0.31591188140651166, 0.648466936215357, 1.0993782391344866, 1.6451284697769106, 2.25463601232057, 2.8947248889603028, 3.534126758562552]
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