TY - JOUR T1 - FPGA donanımı ile biyolojik nöron modellerinin modüler olarak tasarımı ve gerçekleştirimi TT - Modular design and implementation of biological neuron models with FPGA hardware AU - Öztürk, İsmail AU - Doğan, Sılaynur AU - Güneş, Onur PY - 2025 DA - July Y2 - 2025 JF - Kayseri Üniversitesi Mühendislik ve Fen Bilimleri Dergisi JO - KAYÜ J. Eng.and Sci. PB - Kayseri Üniversitesi WT - DergiPark SN - 3108-415X SP - 12 EP - 21 VL - 1 IS - 1 LA - tr AB - Bu çalışmada biyolojik nöron modellerinin dijital donanım gerçekleştirimleri için standart ve modüler bir tasarım yaklaşımı önerilmektedir. Bu tasarım yaklaşımına göre matematiksel denklem, parametre ve sergileyebildiği çalışma modlarına bakmaksızın bütün nöron modellerinin tek bir standart formatta gerçekleştirimi yapılmaktadır. Sonrasında ise aynı formatta gerçekleştirilen nöron modellerinin, donanım üzerinde ayrı ayrı kullanılması yerine bu nöron modelleri tek bir blok yapı içerisinde birleştirilerek aynı anda kullanılabilmektedir. Bu modüler yaklaşım nöromorfik uygulamalarda hızlı prototiplendirme ve tasarım esnekliği sağlamaktadır. Örnek bir tasarım olarak Izhikevich, Fitzhugh-Nagumo (FHN), Hindmarsh–Rose (HR) ve Leaky Integrate-and-Fire (LIF) nöron modelleri seçilmiş ve önerilen yapıda birleştirilmiştir. Önerilen yapının donanım gerçekleştirimi ise FPGA (Field Programmable Gate Array) üzerinde yapılmıştır. Çıkışlar osiloskop ile gözlemlenmiş olup elde edilen sonuçlar simülasyonlar ile uyumludur. KW - Biyolojik nöron modeli KW - FPGA KW - Nöromorfik donanım N2 - In this study, a standard and modular design approach is proposed for digital hardware implementations of biological neuron models. According to this design approach, all neuron models are implemented in a single standard format regardless of mathematical equations, parameters and operating modes they can exhibit. Afterwards, instead of using neuron models implemented in the same format separately on the hardware, these neuron models can be combined into a single block structure and used simultaneously. This modular approach provides rapid prototyping and design flexibility in neuromorphic applications. As an example design, Izhikevich, Fitzhugh-Nagumo (FHN), Hindmarsh–Rose (HR) and Leaky Integrate-and-Fire (LIF) neuron models were selected and combined in the proposed structure. The hardware implementation of the proposed structure was performed on FPGA (Field Programmable Gate Array). The outputs were observed with an oscilloscope and the obtained results are in agreemeent with the simulations. CR - Yang, J. Q., Wang, R., Ren, Y., Mao, J. Y., Wang, Z. P., Zhou, Y., & Han, S. T. (2020). 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