This paper presents a decentralized kernel density estimation (KDE) technique for computing the actual positional density of the robots in a distributed network, which constitutes the feedback in the robot’s control law. The goal of the feedback control law is to plan the paths of a distributed robot network in order to follow a known, optimal time-varying robot distribution or probability dens...

We present an analysis for evaluating the probability density function (pdf) of the noise at the output of the frequency demodulator. It is shown that the noise is non-Gaussian and that for low to medium signal-to-noise power ratios, its pdf differs very significantly from the Gaussian pdf commonly assumed in simplified analysis. These results are very important for analyzing the performance of...

In blind source separation, convergence and separation performance are highly dependent on a relation between a probability density function (pdf) of the output signals y and nonlinear functions f(y) used in updating coefficients of a separation block. This relation was analyzed based on kurtosis κ4 of the output signals. The nonlinear functions, tanh(y) and y have been suggested for super-Gaus...

—In this article we investigate the performance of Orthogonal Frequency Division Multiplexing (OFDM)-based dual-hop Amplify-and-Forward (AF) relay networks in the presence of Phase Noise (PN). A scenario with Rayleigh fading statistics on both hops is assumed. We prove the intercarrier interference is Gaussian random variable firstly, which is recognized by everyone but has not been proved, an...