Research And Application Of Differential Evolution Algorithm In Blind Detection

Differential evolution of differential evolution algorithm is an emerging technology. It has less parameter settings, high efficiency of search, and lower complexity et al. At present, it has been successfully applied to robots, communications, neutral network training and other fields. Blind detection technology is firstly studied intensively 30 years ago. In this technology, the transmitted sequence is estimated without the prior knowledge. First of all, based on differential evolution algorithms this paper gives direct blind signal detection, and analyses algorithm performances. Then because of disadvantages of the algorithm, this paper presents three blind detection algorithms based on improved differential evolution. Finally simulations and complexity of this algorithm show that the improved algorithms have obvious superiority.This paper is organized as follows: Chapter I provides an overview of research on background and the main work of this paper. Chapter II describes the principle and summarization of current works. Chapter III illustrates basic theory about blind equalization technology and blind signal process. Chapter IV gives blind detection algorithm based on differential evolution models, flowcharts and simulation analysis of algorithms. In chapter V three improved algorithms are firstly proposed, which are called blind detection algorithm based on chaos detection algorithm, blind detection algorithm based on self-regulating mutation and blind detection algorithm based on chaos self-regulating mutation. The analysis of these algorithms have been validated by the simulations in terms of the bit error rate, complexity, and convergence. Chapter VI is a summary and outlook.