We formulate an optimal load control (OLC) problem in power networks where the objective is to minimize the aggregate cost of tracking an operating point subject to power balance over the network. We prove that the swing dynamics and the branch power flows, coupled with frequency-based load control, serve as a distributed primal-dual algorithm to solve OLC. Even though the system has multiple e...

In this paper, a recursive least squares (RLS) based blind adaptive beamforming algorithm that features a new variable forgetting factor (VFF) mechanism is presented. The beamformer is designed according to the constrained constant modulus (CCM) criterion, and the proposed adaptive algorithm operates in the generalized sidelobe canceler (GSC) structure. A detailed study of its operating propert...

In this paper, a recursive least squares (RLS) based blind adaptive beamforming algorithm that features a new variable forgetting factor (VFF) mechanism is presented. The beamformer is designed according to the constrained constant modulus (CCM) criterion, and the proposed adaptive algorithm operates in the generalized sidelobe canceler (GSC) structure. A detailed study of its operating propert...

Non-Bayesian parameter estimation under parametric constraints is encountered in numerous applications in signal processing, communications, and control. Mean-squared-error (MSE) lower bounds are widely used as performance benchmarks and for system design. The well-known constrained Cramér-Rao bound (CCRB) is a lower bound on the MSE of estimators that satisfy some unbiasedness conditions. In m...

background: the concept of organizational learning capability (olc) emphasizes the importance of facilitating factors for organizational learning or the organizational propensity to learn. consequently, measures of olc have traditionally determined their dimensions or facilitating factors based on the literature. the purpose of this study was to validate and evaluate the factorial construction ...