@misc{Zhang_Ye_Design_2024,
 author={Zhang, Ye and Wang, Ruiting and Zhang, Yejin and Su, Yanmei and Wang, Pengfei and Luo, Guangzhen and Zhou, Xuliang and Pan, Jiaoqing},
 contributor={Urbańczyk, Wacław. Redakcja},
 identifier={DOI: 10.37190/oa240101},
 year={2024},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 publisher={Oficyna Wydawnicza Politechniki Wrocławskiej},
 description={Optica Applicata, Vol. 54, 2024, nr 1, s. 5-13},
 description={Optica Applicata is an international journal, published in a non-periodical form in the years 1971-1973 and quarterly since 1973. From the beginning of the year 2008, Optica Applicata is an Open Access journal available online via the Internet, with free access to the full text of articles serving the best interests of the scientific community. The journal is abstracted and indexed in: Chemical Abstracts, Compendex, Current Contents, Inspec, Referativnyj Zhurnal, SCI Expanded, Scopus, Ulrich’s Periodicals Directory},
 description={http://opticaapplicata.pwr.edu.pl/},
 language={eng},
 abstract={In recent years, optical neural networks have attracted widespread attention, due to their advantages of high speed, high parallelism, high bandwidth, and low power consumption. Photonic unitary neural network is a kind of neural networks that utilize the principles of unitary matrices and photonics to perform computations. In this paper, we design a photonic unitary neural network based on Mach–Zehnder interferometer arrays. The results show that the network has a good performance on both triangular and circular binary classification datasets, where most of the data points are correctly classified. The accuracies achieve 97% and 95% for triangular and circular datasets, with the loss function values of 0.023 and 0.046, respectively.},
 type={artykuł},
 title={Design of a photonic unitary neural network based on MZI arrays},
 keywords={optyka, optical neural network, unitary matrix, Mach–Zehnder interferometer},
}