304 research outputs found
KYP Lemma for Non-Strict Inequalities and the associated Minimax Theorem
Several variations of the classical Kalman-Yakubovich-Popov Lemma, as well
the associated minimax theorem are presented.Comment: 24 page
Designing Optimal Quantum Detectors Via Semidefinite Programming
We consider the problem of designing an optimal quantum detector to minimize
the probability of a detection error when distinguishing between a collection
of quantum states, represented by a set of density operators. We show that the
design of the optimal detector can be formulated as a semidefinite programming
problem. Based on this formulation, we derive a set of necessary and sufficient
conditions for an optimal quantum measurement. We then show that the optimal
measurement can be found by solving a standard (convex) semidefinite program
followed by the solution of a set of linear equations or, at worst, a standard
linear programming problem. By exploiting the many well-known algorithms for
solving semidefinite programs, which are guaranteed to converge to the global
optimum, the optimal measurement can be computed very efficiently in polynomial
time.
Using the semidefinite programming formulation, we also show that the rank of
each optimal measurement operator is no larger than the rank of the
corresponding density operator. In particular, if the quantum state ensemble is
a pure-state ensemble consisting of (not necessarily independent) rank-one
density operators, then we show that the optimal measurement is a pure-state
measurement consisting of rank-one measurement operators.Comment: Submitted to IEEE Transactions on Information Theor
Global analysis of piecewise linear systems using impact maps and surface Lyapunov functions
This paper presents an entirely new constructive global analysis methodology for a class of hybrid systems known as piecewise linear systems (PLS). This methodology infers global properties of PLS solely by studying the behavior at switching surfaces associated with PLS. The main idea is to analyze impact maps, i.e., maps from one switching surface to the next switching surface. Such maps are known to be "unfriendly" maps in the sense that they are highly nonlinear, multivalued, and not continuous. We found, however, that an impact map induced by an linear time-invariant flow between two switching surfaces can be represented as a linear transformation analytically parametrized by a scalar function of the state. This representation of impact maps allows the search for surface Lyapunov functions (SuLF) to be done by simply solving a semidefinite program, allowing global asymptotic stability, robustness, and performance of limit cycles and equilibrium points of PLS to be efficiently checked. This new analysis methodology has been applied to relay feedback, on/off and saturation systems, where it has shown to be very successful in globally analyzing a large number of examples. In fact, it is still an open problem whether there exists an example with a globally stable limit cycle or equilibrium point that cannot be successfully analyzed with this new methodology. Examples analyzed include systems of relative degree larger than one and of high dimension, for which no other analysis methodology could be applied. This success in globally analyzing certain classes of PLS has shown the power of this new methodology, and suggests its potential toward the analysis of larger and more complex PLS
Stable Nonlinear Identification From Noisy Repeated Experiments via Convex Optimization
This paper introduces new techniques for using convex optimization to fit
input-output data to a class of stable nonlinear dynamical models. We present
an algorithm that guarantees consistent estimates of models in this class when
a small set of repeated experiments with suitably independent measurement noise
is available. Stability of the estimated models is guaranteed without any
assumptions on the input-output data. We first present a convex optimization
scheme for identifying stable state-space models from empirical moments. Next,
we provide a method for using repeated experiments to remove the effect of
noise on these moment and model estimates. The technique is demonstrated on a
simple simulated example
- …