AW-SOM, an Algorithm for High-Speed Learning in Hardware Self-Organizing Maps
Author:
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/8920/8974448/08681156.pdf?arnumber=8681156
Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Wind power forecasting system with data enhancement and algorithm improvement;Renewable and Sustainable Energy Reviews;2024-05
2. SESOMP: A Scalable and Energy-Efficient Self-Organizing Map Processor with Computing-In-Memory and Dead Neuron Pruning;2023 IEEE Asian Solid-State Circuits Conference (A-SSCC);2023-11-05
3. Place-and-Route Analysis of FPGA Implementation of Nested Hardware Self-Organizing Map Architecture;Electronics;2023-11-03
4. A Hardware-Oriented QAM Demodulation Method Driven by AW-SOM Machine Learning;2023 57th Asilomar Conference on Signals, Systems, and Computers;2023-10-29
5. Implementing in-situ self-organizing maps with memristor crossbar arrays for data mining and optimization;Nature Communications;2022-04-28
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