Nonuniform Phased Sampling method is proposed to phase-only synthesize the power pattern of both linear and planar antenna arrays. This method modifies the conventional sampling method which is used for amplitude-phase synthesis. This method is based on assigning suitable phases to the sampling points of radiation pattern in order to reach desired amplitude of currents. Some examples are given ...

The design and performance analysis of bandit algorithms in the presence stage-wise safety or reliability constraints has recently garnered significant interest. In this work, we consider linear stochastic problem under additional unknown that need to be satisfied at each round. For problem, present analyze a new safe algorithm based on Thompson Sampling (TS). Our shows that, with high probabil...

a new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. we use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. then, we linearized this identified model at each sampling time to have an approximate linear time varying system. in order to stabilize...

Consider the inverse acoustic scattering of time-harmonic point sources by a locally perturbed interface with buried obstacles in lower half-space. A novel version sampling method is proposed to simultaneously reconstruct local perturbation rough and constructing modified near-field equation associated special surface, yielding fast imaging algorithm. Numerical examples are presented illustrate...

In this paper, the problem of nonfragile reliable guaranteed cost control for networked control systems with time-varying sampling period sensors and actuator failures is concerned for a given quadratic cost function. For linear time-invariant controlled plant, under the assumption that the sampling period is time-varying within a certain known bound, the time delay is constant and shorter than...

We present a new sampling approach to Bayesian learning of the Bayesian network structure. Like some earlier sampling methods, we sample linear orders on nodes rather than directed acyclic graphs (DAGs). The key difference is that we replace the usual Markov chain Monte Carlo (MCMC) method by the method of annealed importance sampling (AIS). We show that AIS is not only competitive to MCMC in e...