A distributed discrete-time algorithm is proposed for multi-agent networks to achieve a common least squares solution of a group of linear equations, in which each agent only knows some of the equations and is only able to receive information from its nearby neighbors. For fixed, connected, and undirected networks, the proposed discrete-time algorithm results in each agents solution estimate to...

This paper presents an example of solving the parameter identification problem in case a robot with two degrees freedom. In this study, weighted recursive least squares algorithm was generalised to nonlinear parameterisation which identified parameters did not satisfy linear model. The generalisation involved linearising model neighbourhood current values estimates. It assumed that estimates we...

Due to widespread use of Global Positioning System (GPS) in different applications, the issue of GPS signal interference cancelation is becoming an increasing concern. One of the most important intentional interferences is spoofing signals. An effective interference (delay spoof) reduction method based on adaptive filtering is developed in this paper. The principle of method is using adaptive f...

The behavior of variable step-size least-mean-square (VSSLMS) algorithms is strongly affected by measurement noise. Thereby, aiming to maintain an adequate performance of these algorithms, their parameters must be adjusted whenever changes occur in the signal-to-noise ratio (SNR) of the adaptive system. A well-known VSSLMS algorithm based on error correlation provides a performance enhancement ...

A novel algorithm is developed based on fractional signal processing approach for parameter estimation of input nonlinear control autoregressive (INCAR) models. The design scheme consists of parameterization of INCAR systems to obtain linear-in-parameter models and to use fractional least mean square algorithm (FLMS) for adaptation of unknown parameter vectors. The performance analyses of the p...

In this paper, a modified estimation algorithm has been developed refers to Covariance Shaping Least Square (CSLS) estimation based on the quantum mechanical concepts and constraints. The algorithm has been applied to Auto Regressive Moving Average (ARMA models with various parameter values. The same models can be applied with Colored Noise which estimates the bias in the parameter and the vali...

We consider parameter estimation in linear models when some of the parameters are known to be integers. Such problems arise, for example, in positioning using phase measurements in the global positioning system (GPS.) Given a linear model, we address two problems: 1. The problem of estimating the parameters. 2. The problem of verifying the parameter estimates. Under Gaussian measurement noise: ...

at first, ground-based circular strip-map synthetic aperture radar (gb-csmsar) and its capabilities is introduced and the received signal model, 2-d frequency spectrum and the azimuth and range resolutions are derived and compared with the linear motion strip-map sar resolutions. because of the stability of the path and speed of antenna in gb-csmsar a frequency domain imaging algorithm is sugge...

This paper proves the effectiveness of Least Mean Square (LMS) estimation algorithm for estimation of power system harmonics, inter-harmonics and sub-harmonics of distorted signal. Accurate estimation can be achieved by this technique for harmonics, sub-harmonics and inter-harmonics estimation including possible variation in the signal such as change in amplitude when applied to a distorted pow...