Results 151 to 160 of about 68,095 (317)

COMPLEX DATA CLUSTERING WITH SINGLE-LAYER DYNAMICALLY LINKED SPIKING NEURAL NETWORK

Advanced Engineering Research, 2010
An improved method for constructing and training single-layered spiking neural networks is preposed. The method allows to apply single-layered spiking neural networks that encode each data dimension by one neuron of the input layer for the recognition of
A.A. KRASNOSHCHEKOV
doaj  

A Preliminary Study on Connectivism—Constructivism Learning Theory Based on Developmental Cognitive Neuroscience and Spiking Neural Network

, 2021
Xin Liu, Huailong Li
openalex   +2 more sources

Evolutionary spiking neural networks: a survey

Journal of Membrane Computing
Spiking neural networks (SNNs) are gaining increasing attention as potential computationally efficient alternatives to traditional artificial neural networks(ANNs). However, the unique information propagation mechanisms and the complexity of SNN neuron models pose challenges for adopting traditional methods developed for ANNs to SNNs.
Shen, Shuaijie, Zhang, Rui, Wang, Chao, Huang, Renzhuo, Tuerhong, Aiersi, Guo, Qinghai, Lu, Zhichao, Zhang, Jianguo, Leng, Luziwei   +8 more
openaire   +2 more sources

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

COMPLEX DATA CLUSTERING WITH SINGLE-LAYER DYNAMICALLY LINKED SPIKING NEURAL NETWORK

Вестник Донского государственного технического университета, 2018
An improved method for constructing and training single-layered spiking neural networks is preposed. The method allows to apply single-layered spiking neural networks that encode each data dimension by one neuron of the input layer for the recognition of
A.A. KRASNOSHCHEKOV
doaj  

Heterogeneous quantization regularizes spiking neural network activity [PDF]

Roy Moyal, Kyrus R. Mama, Matthew Einhorn, Ayon Borthakur, Thomas A. Cleland   +4 more
openalex   +1 more source

Paired Competing Neurons Improving STDP Supervised Local Learning In Spiking Neural Networks [PDF]

, 2023
Gaspard Goupy, Tirilly, Pierre, Bilasco, Ioan Marius   +2 more
openalex   +1 more source

Smart REASSURED Sensors via Machine‐Augmented Printable On‐Paper Arrays

Advanced Sensor Research, EarlyView.
This perspective highlights the emerging role of pattern‐recognition, printable on‐paper sensor arrays for intelligent PoC diagnostics. It discusses how paper's inherent limitations can be overcome through surface modification and scalable printing, and how machine‐learning analysis of cross‐reactive arrays enables multiplexed, low‐cost, and REASSURED ...
Naimeh Naseri, Saba Ranjbar
wiley   +1 more source

Electronic Nose for Indoor Mold Detection and Identification

Advanced Sensor Research, EarlyView.
This study explores the potential of a SnO2 nanowire‐based chemiresistive electronic nose not only to detect but also to identify two common indoor mold species, Stachybotrys chartarum and Chaetomium globosum on two different growth substrates. In a laboratory setup, the electronic nose displays high classification performance using optimized linear ...
Hankun Yang, Martin Sommer, Stephanie Bauer, Uli Lemmer   +3 more
wiley   +1 more source

Classifying Images with CoLaNET Spiking Neural Network -- the MNIST Example [PDF]

Mikhail Kiselev
openalex   +1 more source