Applying B-Spline Biorthogonal Wavelet Basis Functions to the Method of Moments in Solving Poisson equation

The aim of this paper is to introduce the application of B-spline biorthogonal wavelet with various orders (number of vanishing moments) in Electrostatic problems and making improvement in the moment method development. Due to the order of wavelet, the impedance matrix resulting in this problem is sparsified by wavelet, and consequently, the solution can be obtained rapidly. To illustrate these concepts, the two-body problem of parallel square conducting plates is presented. To demonstrate the effectiveness and accuracy of the proposed technique, numerical results for charge density potential, capacity, and error relative for different order of B-spline biorthogonal wavelets and dielectric constant are presented. Results are compared to the previous work done and published, excellent results are obtained

A Comparison Study of PAPR Reduction in OFDM Systems Based on Swarm Intelligence Algorithms

Optimization algorithms have been one of the most important research topics in Computational Intelligence Community. They are widely utilized mathematical functions that solve optimization problems in a variety of purposes via the maximization or minimization of a function. The swarm intelligence (SI) optimization algorithms are an active branch of Evolutionary Computation, they are increasingly becoming one of the hottest and most important paradigms, several algorithms were proposed for tackling optimization problems. The most respected and popular SI algorithms are Ant colony optimization (ACO) and particle swarm optimization (PSO). Fireworks Algorithm (FWA) is a novel swarm intelligence algorithm, which seems effective at finding a good enough solution of a complex optimization problem. In this chapter we proposed a comparison study to reduce the high PAPR (Peak-to-Average Power Ratio) in OFDM systems based on the swarm intelligence algorithms like simulated annealing (SA), particle swarm optimization (PSO), fireworks algorithm (FWA), and genetic algorithm (GA). It turns out from the results that some algorithms find a good enough solutions and clearly outperform the others candidates in both convergence speed and global solution accuracy