parameter estimation is an important task in the modeling, classification, and detection of radar clutters. radar clutters have stochastic characteristics. therefore, statistical distributions are usually used to describe the features of clutters better. k distribution is one of the most common models utilized to the simulation of clutters. this distribution, which consists of scale and shape p...

The power spectrum of a zero-mean stationary Gaussian random process is assumed to be known except for one or more parameters which are to be estimated from an observation of the process during a finite time interval. The approximation is introduced that the coefficients of the Fourier series expansion of a realization of long-time duration are uncorrelated. Based on this approximation maximum ...

in the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. in this study, hydrodynamic coefficients of an autonomous un...

-  Power system state estimation is a central component in energy management systems of power system. The goal of state estimation is to determine the system status and power flow of transmission lines. This paper presents an advanced state estimation algorithm based on weighted least square (WLS) criteria by introducing virtual meters. For each bus of network, except slack bus, a virtual meter...

Load forecasting allows for the utilities to plan their operations to serve their customers with more reliable and economical electric power. With the developments in computer and information technology new techniques to accurately forecast power system loading are emerging. This research culminates in development of modified algorithms for short-term load forecasting (STLF) of a utility grade ...

Knowledge of the parameter values of the dynamic generator models is of paramount importance for creating accurate models for power system dynamics studies. Traditionally, power systems consists of a relatively limited numbers of large power stations and the values of generator parameters were provided by manufacturers and validated by utilities. Recently however, with the increasing penetratio...

The Power-Law Process (PLP) is a two-parameter model widely used for modeling repairable system reliability. Results on exact point estimation for both parameters as well as exact interval estimation for the shape parameter are well-known. In this paper, we investigate the interval estimation for the scale parameter. Asymptotic confidence intervals are derived using Fisher information matrix an...