The ability of a robot team to reconfigure itself is useful in many applications: for metamorphic robots to change shape, for swarm motion towards a goal, for biological systems to...
Peng Yang, Randy A. Freeman, G. J. Gordon, Kevin M...
: In this paper, two nonlinear optimization methods for the identification of nonlinear systems are compared. Both methods estimate all the parameters of a polynomial nonlinear sta...
Anne Van Mulders, Johan Schoukens, Marnix Volckaer...
When a phenomenon is described by a parametric model and multiple datasets are available, a key problem in statistics is to discover which datasets are characterized by the same p...
This paper describes a new kernel-based approach for linear system identification of stable systems. We model the impulse response as the realization of a Gaussian process whose s...
Linear System Identification yields a nominal model parameter, which minimizes a specific criterion based on the single inputoutput data set. Here we investigate the utility of va...