public void enableInputCentering(final int i) {
final SignalSmoother avgInput = new SignalSmoother(1.0 - this.inertia);
if (this.inertia == 1.0) {
avgInput.freeze();
}
this.avgInputs.set(i, avgInput);
}
private Vector input(final Vector x, final boolean update) {
final Vector result = x.copy();
for (int i = 0; i < this.avgInputs.size(); i++) {
final SignalSmoother avgInput = this.avgInputs.get(i);
if (avgInput != null) {
if (update) {
final double oldAvgInput = avgInput.getSmoothedValue();
avgInput.addValue(x.get(i));
this.offset += this.coefficients.get(i) * (avgInput.getSmoothedValue() - oldAvgInput);
}
result.add(i, -avgInput.getSmoothedValue());
}
}
return result;
}
/**
* Sets the inertia of this regression to the given value.
*
* @param inertia the new intertia; must be in (0, 1]
*/
public void setInertia(final double inertia) {
if (inertia <= 0 || inertia > 1) {
throw new IllegalArgumentException("lambda must be in (0,1]");
}
this.inertia = inertia;
for (int i = 0; i < this.avgInputs.size(); i++) {
final SignalSmoother avgInput = this.avgInputs.get(i);
if (avgInput != null) {
if (inertia < 1.0) {
avgInput.setInnovationWeight(1.0 - inertia);
} else {
avgInput.freeze();
}
}
}
}
