Results 101 to 110 of about 22,581 (258)

RFI detection with spiking neural networks

Publications of the Astronomical Society of Australia
AbstractDetecting and mitigating radio frequency interference (RFI) is critical for enabling and maximising the scientific output of radio telescopes. The emergence of machine learning (ML) methods capable of handling large datasets has led to their application in radio astronomy, particularly in RFI detection.
N.J. Pritchard, A. Wicenec, M. Bennamoun, R. Dodson   +3 more
openaire   +2 more sources

In Situ Integrated Titanium Oxide Synaptic Phototransistor Enabling Multimodal Plasticity and Noise‐Robust Selective Attention

Advanced Materials Technologies, EarlyView.
An in situ integrated TiO2/SiOx/Al2O3 synaptic phototransistor couples ultraviolet and electrical stimuli within a scalable, CMOS‐compatible oxide stack. Multimodal plasticity, spike‐timing‐dependent learning, and bee‐inspired associative conditioning are achieved through trap‐mediated temporal dynamics.
Youngbin Yoon, Jaehee Lee, Jeongwook Kwon, Yongki Kim, Myunghun Shin, Jung Wook Lim   +5 more
wiley   +1 more source

Directional Latent Hybridization: Beyond Random Noise in Physics‐Informed Generative Inverse Design of Nonlinear Metamaterials

Advanced Materials Technologies, EarlyView.
A physics‐informed generative framework introduces Directional Latent Hybridization (DLH) for the deterministic inverse design of nonlinear metamaterials. By hybridizing dominant traits from parent geometries in the latent space, DLH overcomes the instabilities of stochastic models to ensure high structural precision at high densities.
Semin Ahn, Jun Young Choi, Sung‐Hoon Ahn   +2 more
wiley   +1 more source

On‐Chip Photonic Neural Network Architectures

Advanced Optical Materials, EarlyView.
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong, Berkay Neseli, Seungyeon Cho, Seungsoo Lee, Yeonjun Kim, Seungyoon Choi, Hyo‐Hoon Park, Hamza Kurt   +7 more
wiley   +1 more source

SNNtrainer3D: Training Spiking Neural Networks Using a User-Friendly Application with 3D Architecture Visualization Capabilities

Applied Sciences
Spiking Neural Networks have gained significant attention due to their potential for energy efficiency and biological plausibility. However, the reduced number of user-friendly tools for designing, training, and visualizing Spiking Neural Networks ...
Sorin Liviu Jurj, Sina Banasaz Nouri, Jörg Strutwolf   +2 more
doaj   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source

Adaptive spatiotemporal neural networks through complementary hybridization

Nature Communications
Processing spatiotemporal data sources with both high spatial dimension and rich temporal information is a ubiquitous need in machine intelligence. Recurrent neural networks in the machine learning domain and bio-inspired spiking neural networks in the ...
Yujie Wu, Bizhao Shi, Zhong Zheng, Hanle Zheng, Fangwen Yu, Xue Liu, Guojie Luo, Lei Deng   +7 more
doaj   +1 more source

Spiking Neural Models of Neurons and Networks for Perception, Learning, Cognition, and Navigation: A Review

Brain Sciences
This article reviews and synthesizes highlights of the history of neural models of rate-based and spiking neural networks. It explains that theoretical and experimental results about how all rate-based neural network models, whose cells obey the membrane
Stephen Grossberg
doaj   +1 more source

Multimodal Locomotion in Insect‐Inspired Microrobots: A Review of Strategies for Aerial, Surface, Aquatic, and Interfacial Motion

Advanced Robotics Research, EarlyView.
This review identifies key design considerations for insect‐inspired microrobots capable of multimodal locomotion. To draw inspiration, biological and robotic strategies for moving in air, on water surfaces, and underwater are examined, along with approaches for crossing the air–water interface.
Mija Jovchevska, Kaushik Jayaram, Nicole Xu   +2 more
wiley   +1 more source

Auditory–Tactile Congruence for Synthesis of Adaptive Pain Expressions in RoboPatients

Advanced Robotics Research, EarlyView.
In this work, we explore auditory–tactile congruence for synthesizing adaptive vocal pain expressions in robopatients. Using a robopatient platform that integrates vocal pain sounds with palpation forces, we conducted 7680 trials across 20 participants.
Saitarun Nadipineni, Chapa Sirithunge, Yue Xie, Fumiya Iida, Thilina Dulantha Lalitharatne   +4 more
wiley   +1 more source