𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A real-time approach to array control based on a learned genetic algorithm

✍ Scribed by Salvatore Caorsi; Massimo Donelli; Andrea Lommi; Andrea Massa


Publisher
John Wiley and Sons
Year
2003
Tongue
English
Weight
409 KB
Volume
36
Category
Article
ISSN
0895-2477

No coin nor oath required. For personal study only.

✦ Synopsis


Abstract

In the framework of wireless communications, it is mandatory to guarantee the reliability of the receiver by assuring good quality at the end‐user, in order to successfully decode transmitted signals. To this end, a method for the design of adaptive antenna arrays is described in this paper. The proposed procedure, based on a customized genetic algorithm, allows real‐time control of the receiver's performance by acting on the discretized phase coefficients of the array elements. As a result, at the receiver, multiple and alternating interferences are considerably reduced with respect to the desired signal. In order to validate the proposed strategy, selected numerical results, concerning various environment conditions, are presented and deeply discussed. Β© 2003 Wiley Periodicals, Inc. Microwave Opt Technol Lett 36: 235–238, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10731


πŸ“œ SIMILAR VOLUMES


A self-learning and tuning fuzzy logic c
✍ Hung-Yuan Chung; Chih-Kuan Chiang πŸ“‚ Article πŸ“… 1997 πŸ› John Wiley and Sons 🌐 English βš– 237 KB πŸ‘ 2 views

This article presents a new method for learning and tuning a fuzzy logic controller automatically. A reinforcement learning and a genetic algorithm are used in conjunction with a multilayer neural network model of a fuzzy logic controller, which can automatically generate the fuzzy control rules and

A genetic algorithm with deterministic m
✍ Minoru Fukumi; Norio Akamatsu πŸ“‚ Article πŸ“… 1998 πŸ› John Wiley and Sons 🌐 English βš– 189 KB πŸ‘ 2 views

This paper presents a method for designing neural networks using a genetic algorithm (GA) with deterministic mutation (DM) based on learning. The GA presented in this paper has a large framework including DM, which is performed on the basis of the results from neural network learning. It can achieve

A Genetic-Algorithm Approach to Scheduli
✍ Jack M. West; John K. Antonio πŸ“‚ Article πŸ“… 2002 πŸ› Elsevier Science 🌐 English βš– 298 KB

Computational efficiency is of great significance for high-performance embedded applications. The work here develops and evaluates a geneticalgorithm-based (GA-based) optimization technique for the scheduling of messages for a class of parallel embedded signal processing techniques known as space-ti