The denoising of a natural image corrupted by additive white Gaussian noise (AWGN) is a classical problem in the signal processing community. The corruption of an image by noise is common during its acquisition or transmission. The aim of denoising is to remove the noise while keeping the signal featuresas much as possible. Traditional algorithms, such as the standard median (SM) filter and mea...

this paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (mimo) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. the agents may have different dynamics and communicate together under a directed graph. a distributed adaptive method is designed for both cases. the structures of the contro...

In this paper, a novel method for selecting a navigation satellite subset for a global positioning system (GPS) based on a genetic algorithm is presented. This approach is based on minimizing the factors in the geometric dilution of precision (GDOP) using a modified genetic algorithm (MGA) with an elite conservation strategy, adaptive selection, adaptive mutation, and a hybrid genetic algorithm...

The rapid development in the area of cognitive radio technology leads the society to higher standards of spectrum sensing performance, particularly in low signal-to-noise ratio (SNR) environment. This article proposes an adaptive double-threshold energy sensing method based on Markov model (ADEMM). When using the double-threshold energy sensing method, the modified Markov model that accounts fo...

abstract according to the adventages of passive radars they have been reconsidered recently due to development of signal processing technology. in the field of sea targets detection using passive radar few research have been reported. this paper presents a new method to detect sea targets using adaptive filter weights variation model and using the fact that the radar cross section of sea target...

A new adaptive regression type of image destriping method is introduced to reconstruct missing lines in mul-tispectral images. The method uses available information from the failed pixel surrounding due to spectral and spatial correlation of multispectral data. The reconstruction is based on two mutually competing adaptive regression models from which the locally optimal predictor is selected.

An adaptive noise cancellation scheme for speech processing is described, in which adaptive filters operate in frequency–limited sub–bands. Previously the filters had been distributed in a linear fashion in the frequency domain. This work investigates the effects of spacing the filters more in sympathy with the signal power and spectral characteristics. It is found that improvements in signal–t...

In this study, a new adaptive controller is proposed for position control of pneumatic systems. Difficulties associated with the mathematical model of the system in addition to the instability caused by Pulse Width Modulation (PWM) in the learning-based controllers using gradient descent, motivate the development of a new approach for PWM pneumatics. In this study, two modified Feedback Error L...

Particle Swarm Optimization (PSO) is a metaheuristic optimization algorithm that owes much of its allure to its simplicity and its high effectiveness in solving sophisticated optimization problems. However, since the performance of the standard PSO is prone to being trapped in local extrema, abundant variants of PSO have been proposed by far. For instance, Fuzzy Adaptive PSO (FAPSO) algorithms ...