Optoelectronic reservoir computing based on complex-value encoding  

作　　者：Chunxu Ding Rongjun Shao Jingwei Li Yuan Qu Linxian Liu Qiaozhi He Xunbin Wei Jiamiao Yang 

机构地区：[1]Shanghai Jiao Tong University,School of Electronic Information and Electrical Engineering,Shanghai,China [2]Huawei Technologies Co.,Ltd.,Shenzhen,China [3]Shanghai Jiao Tong University,Institute of Marine Equipment,Shanghai,China [4]Shanxi University,School of Automation and Software Engineering,Taiyuan,China [5]Peking University,Biomedical Engineering Department and International Cancer Institute,Beijing,China

出　　处：《Advanced Photonics Nexus》2024年第6期47-54,共8页先进光子学通讯(英文)

基　　金：the National Natural Science Foundation of China(Grant Nos.62375171,62305208,62205189,62105203,and 62405182);the Shanghai Pujiang Program(Grant No.22PJ1407500);the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(SJTU)(Grant No.SL2022ZD205);the National Key Research and Development Program of China(Grant No.2022YFC2806600);the Science Foundation of Donghai Laboratory(Grant Nos.DH-2022KF01001 and DH-2022KF01005);the Startup Fund for Young Faculty at SJTU(Grant No.24X010500120);the Science and Technology Commission of Shanghai Municipality(Grant No.20DZ2220400).

摘　　要：Optical reservoir computing(ORC)offers advantages,such as high computational speed,low power consumption,and high training speed,so it has become a competitive candidate for time series analysis in recent years.The current ORC employs single-dimensional encoding for computation,which limits input resolution and introduces extraneous information due to interactions between optical dimensions during propagation,thus constraining performance.Here,we propose complex-value encoding-based optoelectronic reservoir computing(CE-ORC),in which the amplitude and phase of the input optical field are both modulated to improve the input resolution and prevent the influence of extraneous information on computation.In addition,scale factors in the amplitude encoding can fine-tune the optical reservoir dynamics for better performance.We built a CE-ORC processing unit with an iteration rate of up to∼1.2 kHz using high-speed communication interfaces and field programmable gate arrays(FPGAs)and demonstrated the excellent performance of CE-ORC in two time series prediction tasks.In comparison with the conventional ORC for the Mackey–Glass task,CE-ORC showed a decrease in normalized mean square error by∼75%.Furthermore,we applied this method in a weather time series analysis and effectively predicted the temperature and humidity within a range of 24 h.

关 键 词：optical reservoir computing complex-value encoding time series analysis weather forecast 

分 类 号：G63[文化科学—教育学]