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Mostrando ítems 11-13 de 13
Artículo
How Frequency Injection Locking Can Train Oscillatory Neural Networks to Compute in Phase
(IEEE, 2022)
Brain-inspired computing employs devices and architectures that emulate biological functions for more adaptive and energy-efficient systems. Oscillatory neural networks (ONNs) are an alternative approach in emulating ...
Artículo
PACOSYT: A Passive Component Synthesis Tool Based on Machine Learning and Tailored Modeling Strategies Towards Optimal RF and mm-Wave Circuit Designs
(Institute of Electrical and Electronics Engineers, 2023)
In this paper, the application of regression-based supervised machine learning (ML) methods to the modeling of integrated inductors and transformers is examined. Different ML techniques are used and compared to improve ...
Artículo
Digital Implementation of Oscillatory Neural Network for Image Recognition Applications
(Frontiers Media, 2021)
Computing paradigm based on von Neuman architectures cannot keep up with the ever-increasing data growth (also called “data deluge gap”). This has resulted in investigating novel computing paradigms and design approaches ...