This is the MATLAB code for the implementation of neural pupil engineering FPM (NePE-FPM), an optimization framework for FPM reconstruction for off-axis areas. NePE-FPM engineers the pupil function ...

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require. When you purchase through links on our site, we may earn an affiliate ...

Abstract: The study presents the application of Artificial Neural Networks (ANNs) for pattern recognition, modeling, and analyzing their performance using MATLAB. Two neural architectures are compared ...

Brain-computer interfaces (BCIs) leverage EEG signal processing to enable human-machine communication and have broad application potential. However, existing deep learning-based BCI methods face two ...

Neural networks aren’t the only game in artificial intelligence, but you’d be forgiven for thinking otherwise after the hot streak sparked by ChatGPT’s arrival in 2022. That model’s abilities, ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

The brain criticality hypothesis has been a central research topic in theoretical neuroscience for two decades. This hypothesis suggests that the brain operates near the critical point at the boundary ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...

Computational systems have to learn when and how they should exert control over their actions. How do agents learn to solve this “metacontrol” problem? Here, we created a task that externalizes this ...