Multi-Objective Bacterial Foraging Optimization Algorithm Based on Effective Area in Cognitive Emergency Communication Networks

Cognitive emergency communication net-works can meet the requirements of large capac-ity,high density and low delay in emergency com-munications.This paper analyzes the properties of emergency users in cognitive emergency communi-cation networks,designs a multi-objective optimiza-tion and proposes a novel multi-objective bacterial foraging optimization algorithm based on effective area(MOBFO-EA)to maximize the transmission rate while maximizing the lifecycle of the network.In the algorithm,the effective area is proposed to prevent the algorithm from falling into a local optimum,and the diversity and uniformity of the Pareto-optimal solu-tions distributed in the effective area are used to eval-uate the optimization algorithm.Then,the dynamic preservation is used to enhance the competitiveness of excellent individuals and the uniformity and diversity of the Pareto-optimal solutions in the effective area.Finally,the adaptive step size,adaptive moving direc-tion and inertial weight are used to shorten the search time of bacteria and accelerate the optimization con-vergence.The simulation results show that the pro-posed MOBFO-EA algorithm improves the efficiency of the Pareto-optimal solutions by approximately 55%compared with the MOPSO algorithm and by approx-imately 60%compared with the MOBFO algorithm and has the fastest and smoothest convergence.

An Improved Immune Genetic Algorithm for Solving the Optimization Problems of Computer Communication Networks

Obtaining the average delay and selecting a route in a communication networkare multi-constrained nonlinear optimization problems . In this paper, based on the immune geneticalgorithm, a new fuzzy self-adaptive mutation operator and a new upside-down code operator areproposed. This improved IGA is further successfully applied to solve optimal problems of computercommunication nets.

Speech Suppression with EEMD_WP

In non-cooperation communication, speech suppression is an important link of aircraft type recognition based on shortwave speech communication. Ensemble mean and ensemble variance for analyzing physical characteristics of aircraft cockpit background sound has been proposed in this paper. Some important peak feature is revealed from the ensemble mean and ensemble variance, which has important guiding significance to further researches on speech suppression of aircraft type recognition based on shortwave speech communication. The two algorithms of speech suppression are proposed which are empirical mode decomposition and wavelet transform(EMD_WT) and the algorithm of ensemble empirical mode decomposition and wavelet packet (EEMD_WP). In the process of speech suppression, EMD_WT produced extra noise pollution, and EEMD_WP kept the aircraft cockpit background sound and weakened the effect of the speech largely. The contrast test proves that EEMD_WP has better performance by in time domain and in frequency domain.