CAJ | 학술논문

为了减少压缩感知中梯度投影稀疏重构法算法(GPSR-BB)的运行时间和迭代次数,有效地提高算法的重构性能,将具有全局搜索能力的粒子群算法应用到 GPSR-BB算法中。利用粒子群优化算法的全局开发能力和GPSR-BB算法的局部搜索能力,加快了算法的收敛速度,减少了算法的迭代次数；通过对 GPSR-BB 算法中线搜索条件的改进,有效地提高了算法的重构精度。仿真实验表明：改进的GPSR-BB算法比传统的GPSR-BB算法运行时间缩短了43%、迭代次数降低了39.7%。在观测维数一定的条件下,改进的 GPSR-BB算法重构成功概率高于传统的算法0.04,重构误差低于传统的0.09,具有较好的重构性能。
위료감소압축감지중제도투영희소중구법산법(GPSR-BB)적운행시간화질대차수,유효지제고산법적중구성능,장구유전국수색능력적입자군산법응용도 GPSR-BB산법중。이용입자군우화산법적전국개발능력화GPSR-BB산법적국부수색능력,가쾌료산법적수렴속도,감소료산법적질대차수；통과대 GPSR-BB 산법중선수색조건적개진,유효지제고료산법적중구정도。방진실험표명：개진적GPSR-BB산법비전통적GPSR-BB산법운행시간축단료43%、질대차수강저료39.7%。재관측유수일정적조건하,개진적 GPSR-BB산법중구성공개솔고우전통적산법0.04,중구오차저우전통적0.09,구유교호적중구성능。
In order to decrease the running time,the number of iteration and effectively improve the recon-struction performance of Gradient Proj ection for Sparse reconstruction-Barzilai-Borwein algorithm,Particle Swarm Optimization which has the global search ability is introduced in it.Using PSO's global development ability and the local search ability of GPSR-BB algorithm,the convergence speed is increased and the run-ning time is reduced.By the improvement of algorithm line search conditions,the reconstruction precision is improved effectively.Simulation results show that the improved GPSR-BB algorithm is shorter than the traditional algorithm by 43% in running time and by 39.7% in number of iteration.With the condition of a certain measurement dimension,the improved GPSR-BB algorithm is higher than the traditional one by 0.04 in average probability of success and lower than the traditional one by 0.09 in reconstruction error.