public KalmanFilter()
{
dataPoints = new List<PointF>();
kalmanPoints = new List<PointF>();
kalFilter = new Kalman(2, 2, 0);
syntheticData = new SyntheticData();
Matrix<float> state = new Matrix<float>(new float[]
{
0.0f, 0.0f
});
kalFilter.CorrectedState = state;
kalFilter.TransitionMatrix = syntheticData.transitionMatrix;
kalFilter.MeasurementNoiseCovariance = syntheticData.measurementNoise;
kalFilter.ProcessNoiseCovariance = syntheticData.processNoise;
kalFilter.ErrorCovariancePost = syntheticData.errorCovariancePost;
kalFilter.MeasurementMatrix = syntheticData.measurementMatrix;
}
//Timer MousePositionTaker = new Timer();
//Timer KalmanOutputDisplay = new Timer();
#endregion
public KalmanFilter()
{
dataPoints = new List <PointF>();
kalmanPoints = new List <PointF>();
kalFilter = new Kalman(2, 2, 0);
syntheticData = new SyntheticData();
Matrix <float> state = new Matrix <float>(new float[]
{
0.0f, 0.0f
});
kalFilter.CorrectedState = state;
kalFilter.TransitionMatrix = syntheticData.transitionMatrix;
kalFilter.MeasurementNoiseCovariance = syntheticData.measurementNoise;
kalFilter.ProcessNoiseCovariance = syntheticData.processNoise;
kalFilter.ErrorCovariancePost = syntheticData.errorCovariancePost;
kalFilter.MeasurementMatrix = syntheticData.measurementMatrix;
}