This paper addresses the problem of multi-target tracking with superpositional sensors, while covariance matrices measurement noise are not known. The proposed method is based on hybrid multi-Bernoulli cardinalized probability hypothesis density (HMB-CPHD) filter, which has been developed for sensors-based known noises. Specifically, we firstly propose Gaussian mixture (GM) implementation HMB-C...

Zntroduction: Nonlinear filters have been found effective in removing different types of noise from images. This is especially the case if the noise corrupting the image is not Gaussian andlor image details are not to be blurred. For this purpose, a number of order statistics based techniques have been proposed [ 11. In this Letter we describe an extension to our work in [2], where we first pro...

This paper explains the dynamic behaviour of ant colony optimization based Hybrid Active Power Filter (HAPF) accomplished for harmonic compensation under varying source/load conditions. ACO based controller is employed to extract fundamental component of current from non-sinusoidal currents of the considered supply system. Ant colony optimization (ACO) is a novel searching technique used in opt...

Particle filters have been widely used in solving nonlinear filtering problems. Proposal Distribution design is a key issue for these methods and has vital effects on simulation results. Various proposal distributions have been proposed to improve the performance of particle filters, but practical situations have encouraged the researchers to design better candidate for proposal distributions i...

In this paper, we study the sensitivity of the Box Gaussian Mixture Filter (BGMF) in hybrid positioning. The idea of BGMF is to split the state space into pieces using parallel planes when necessary and approximate the restriction of a Gaussian component in each piece as a Gaussian. In the sensitivity analysis, we change the distance between the parallel planes and examine how that affects the ...

The Interacting Multiple Model (IMM) estimator is a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation schemes. The model of hybrid system and the IMM algorithm, initially proposed by Blom, may serve as a basis for synthesis of more efficient filters for tracking maneuvering aircraft. In this paper we present a number of specific features o...

In this paper a diagnostic model based on Naive Bayes developed to diagnose erytemato squamous diseases. The hybrid feature selection method, named IGSBFS (Information Gain and Sequential Backward Floating Search), combines the advantages of filters and wrappers to select the optimal feature subset from the original feature set. In IGSBFS, Information Gain acts as filters to remove redundant fe...

A new version of an experimental system of an optoelectronic hybrid optical parallel array logic system is constructed. The experimental system is composed of a two-dimensional correlator with selectable holographic filters and parallel electronic circuits. The system can process images consisting of 3 × 3 pixels at a time. Several types of processing are achieved both without and with dynamic ...