mdof.markov module#
- mdof.markov.okid(inputs, outputs, **options)#
Identify Markov parameters, or discrete impulse response data, for a given set of input and output data. Observer Kalman Identification Algorithm (OKID) [1].
- Parameters:
inputs (array) – input time history. dimensions: \((q,nt)\), where \(q\) = number of inputs, and \(nt\) = number of timesteps
outputs (array) – output response history. dimensions: \((p,nt)\), where \(p\) = number of outputs, and \(nt\) = number of timesteps
m (int, optional) – number of Markov parameters to compute. default: \(min(300, nt)\)
- Returns:
the Markov parameters, with dimensions \((p,q,m+1)\)
- Return type:
array
References#