Frequency-domain characteristic analysis of PCNN-Reference-Cited by-同舟云学术

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Frequency-domain characteristic analysis of PCNN

Published:2023-11-13 Issue: Volume: Page:
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Deng Xiangyu^ORCID,Huang Xikai,Yu Haiyue

Funder

the National Natural Science Foundation of China

the Industrial Support Plan of Education Department of Gansu Province

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s11227-023-05750-x.pdf

Reference27 articles.

1. Eckhorn R, Reitboeck HJ, Arndt MT et al (1990) Feature linking via synchronization among distributed assemblies: Simulations of results from cat visual cortex. Neural Comput 2(3):293–307. https://doi.org/10.1162/neco.1990.2.3.293

2. Johnson JL, Padgett ML (1999) PCNN models and applications. IEEE Trans Neural Networks 10(3):480–498. https://doi.org/10.1109/72.761706

3. Basar S, Waheed A, Ali M et al (2022) An efficient defocus blur segmentation scheme based on hybrid LTP and PCNN. Sensors 22(7):2724. https://doi.org/10.3390/s22072724

4. Biswas B, Ghosh SK, Ghosh A (2020) A novel CT image segmentation algorithm using PCNN and Sobolev gradient algorithms in GPU frameworks. Pattern Anal Appl 23:837–854. https://doi.org/10.1007/s10044-019-00837-9

5. Xiangyu DENG, Yide MA, Min DONG (2016) A new adaptive filtering algorithm for removing salt and pepper noise based on multilayered PCNN. Pattern Recogn Lett 79:8–17. https://doi.org/10.1016/j.patrec.2016.04.019

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