observation update
[x1,y]=system(x0,f,g,h,q,r)
:x0 input state vector : :f system matrix : :g input matrix : :h Output matrix : :q input noise covariance matrix : :r output noise covariance matrix : :x1 output state vector : :y output observation :
define system function which generates the next observation given the old state. System recursively calculated
x1=f*x0+g*u
y=h*x0+v
where u is distributed N(0,q) and v is distribute N(0,r).