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; }