Reconfigurable Cellular Neural Networks and Their Applications
Yazarlar (3)
Müştak E Yalçın
Dr. Öğr. Üyesi Tuba AYHAN Sinop Üniversitesi, Türkiye
Dr. Öğr. Üyesi Ramazan Yeniçeri Sinop Üniversitesi
| Makale Türü | Özgün Makale (Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale) | ||
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| Makale Dili | – | Basım Tarihi | 01-2020 |
| Cilt / Sayı / Sayfa | 0 / 0 / – | DOI | 10.1007/978-3-030-17840-6.pdf |
| Makale Linki | https://link.springer.com/content/pdf/10.1007/978-3-030-17840-6.pdf | ||
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Halı-Kilim ve Dokuma
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| Özet |
| Conventional algorithmic solution for today’s engineering problems is started to digitize the sensory data and then process this raw data on a conventional computer architecture. To obtain real-time response from the algorithms, low latency is required which demands to process huge amount of input data. When the biological sensing systems which can handle the same tasks in real time are considered to mimic nature, they are able to complete processing tasks to extract salient information from the incoming sensory data, thus eliminating the redundant data before transmitting them for subsequent processing for analyzing and making decision. Cellular Neural Network (CNN)[1] which is inspired by architecture of biological networks is reasonable to be used in sensory data processing to extract salient information. Furthermore, its conversion to a many-core microprocessor which is named as CNN-Universal … |
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