Author Affiliations
Abstract
Key Laboratory for Physical Electronics and Devices of the Ministry of Education & Shaanxi Key Laboratory of Information Photonic Technique, Xi’an Jiaotong University, Xi’an 710049, China
We study the parametric amplification of electromagnetically induced transparency-assisted Rydberg six- and eight-wave mixing signals through a cascaded nonlinear optical process in a hot rubidium atomic ensemble both theoretically and experimentally. The shift of the resonant frequency (induced by the Rydberg–Rydberg interaction) of parametrically amplified six-wave mixing signal is observed. Moreover, the interplays between the dressing effects and Rydberg–Rydberg interactions in parametrically amplified multiwave mixing signals are investigated. The linear amplification of Rydberg multiwave mixing processes with multichannel nature acts against the suppression caused by Rydberg–Rydberg interaction and dressing effect.
Rydberg states Nonlinear wave mixing Nonlinear optics, four-wave mixing Nonlinear optics, parametric processes Photonics Research
2018, 6(7): 07000713
1 北京师范大学地表过程与资源生态国家重点实验室, 北京100875
2 北京师范大学环境演变与自然灾害教育部重点实验室, 北京100875
3 北京师范大学数学科学学院, 北京100875
分析了基本粒子群算法(PSO)、 混合粒子群优化算法(HPSO)和模糊C-均值算法(FCM)的特点, 将模糊C-均值算法引入到混合粒子群优化算法中, 发展和改进了HPSO-FCM算法, 并在Fortran语言和MATLAB环境下开发实现HPSO-FCM程序. 以2009年6月份的环境一号卫星多光谱可见光图像和ENVISAT的ASAR微波图像为基础数据, 通过波段叠加和主成分分析, 得到前3个主成分合成图像. 利用HPSO-FCM算法和非监督学习动态聚类算法(ISODATA)分别对湖南东洞庭湖3个主成分合成图像, 进行湿地分类实验. 结果表明:(1)将模糊C-均值算法引入到混合粒子群优化算法中, 具有较好的搜索速度和收敛精度, 能有效寻找和优化最佳聚类中心. (2)HPSO-FCM算法在多光谱遥感图像湿地分类精度比较高, 是一种有效的遥感图像分类方法.
混合粒子群算法 模糊C-均值算法 湿地分类 遥感 Hybrid particle swarm optimization Fuzzy C-means Wetland classification Remote sensing 光谱学与光谱分析
2010, 30(12): 3329