%% Specify Process and Measurement Noise Covariances in Extended Kalman Filter Object
% Create an extended Kalman filter object for a van der Pol oscillator with two states and one output. Use the previously written and saved state transition and measurement functions, vdpStateFcn.m and  vdpMeasurementFcn.m. These functions are written for additive process and measurement noise terms. Specify the initial state values for the two states as [2;0].
% Since the system has two states and the process noise is additive, the process noise is a 2-element vector and the process noise covariance is a 2-by-2 matrix. Assume there is no cross-correlation between process noise terms, and both the terms have the same variance 0.01. You can specify the process noise covariance as a scalar. The software uses the scalar value to create a 2-by-2 diagonal matrix with 0.01 on the diagonals.
% Specify the process noise covariance during object construction.

obj = extendedKalmanFilter(@vdpStateFcn,@vdpMeasurementFcn,[2;0],...
    'ProcessNoise',0.01);

%
% Alternatively, you can specify noise covariances after object construction using dot notation. For example, specify the measurement noise covariance as 0.2.

obj.MeasurementNoise = 0.2;

% Since the system has only one output, the measurement noise is a 1-element vector and the MeasurementNoise property denotes the variance of the measurement noise.
% Copyright 2012 The MathWorks, Inc.