  There exists a vast amount of literature how dissipativity properties can be
exploited to design controllers for stability and performance guarantees for
the closed loop. With the rising availability of data, there has therefore been
an increasing interest in determining dissipativity properties from data as a
means for data-driven systems analysis and control with rigorous guarantees.
Most existing approaches, however, consider dissipativity properties that hold
only over a finite horizon and mostly only qualitative statements can be made
in the presence of noisy data. In this work, we present a novel approach to
determine dissipativity of linear time-invariant systems from data where we
inherently consider properties that hold over the infinite horizon.
Furthermore, we provide rigorous guarantees in the case of noisy state
measurements.
