Akademik Veri Yönetim Sistemi
JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, 2025 (ESCI)
Although the use of artificial neural networks in computer systems has become widespread in many fields, limitations arise in small-scale computers. In resource-constrained small computers, large-scale systems are required for model development and training. In this study, the Diffraction Analysis algorithm has been adapted for small devices, demonstrating the successful designing of an artificial neural network. Real-time diffraction analysis has been conducted using the IRIS, wine and diabetes datasets. This study is anticipated to promote the broader integration of neural networks into edge devices.