Results 81 to 90 of about 2,095,528 (293)

Detecting changes in dynamical structures in synchronous neural oscillations using probabilistic inference

NeuroImage, 2022
Recent neuroscience studies have suggested that cognitive functions and learning capacity are reflected in the time-evolving dynamics of brain networks.
Hiroshi Yokoyama, Keiichi Kitajo
doaj   +1 more source

Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery [PDF]

, 2009
This paper studies a fully Bayesian algorithm for endmember extraction and abundance estimation for hyperspectral imagery. Each pixel of the hyperspectral image is decomposed as a linear combination of pure endmember spectra following the linear mixing ...
Moussaoui, Saïd, N. Dobigeon, Coulon, Martial, Hero, Alfred O., A.O. Hero, Dobigeon, Nicolas, Tourneret, Jean-Yves, M. Coulon, Hero, Alfred, J.-Y. Tourneret, S. Moussaoui   +10 more
core   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Bayesian cue integration as a developmental outcome of reward mediated learning [PDF]

, 2011
Average human behavior in cue combination tasks is well predicted by Bayesian inference models. As this capability is acquired over developmental timescales, the question arises, how it is learned.
Weisswange Thomas H., Rothkopf Constantin A., Weisswange, Thomas H., Tobias Rodemann, Thomas H. Weisswange, Constantin A Rothkopf, Jochen Triesch, Triesch Jochen, Thomas H Weisswange, Rothkopf, Constantin, Constantin A. Rothkopf, Rodemann, Tobias, Triesch, Jochen, Rodemann Tobias   +13 more
core   +2 more sources

Artificial Intelligence Meets Micro/Nanorobotics

Advanced Materials, EarlyView.
Artificial intelligence is transforming micro‐ and nanorobots from externally controlled, task‐specific machines into adaptive, autonomous systems. Machine learning, multimodal perception, digital twins, AI‐guided materials and geometry design enhance propulsion, localization, decision‐making, whichaccelerates clinical and environmental applications ...
Fatma M. Yurtsever, Minitha Cherukutty Ramakrishnan, Ian Kuula Ross, Ivan Zelinka, Hamed Shahsavan, Michal Otyepka, Martin Pumera   +6 more
wiley   +1 more source

Bioengineered Interfaces for Peripheral Nerve Sensory Restoration

Advanced Materials, EarlyView.
Half of amputees abandon their prosthetics for lack of feeling. This review charts the full path from peripheral nerve injury to restored sensation, through surgical, regenerative, noninvasive, and implanted approaches, and shows how injury type and interface material properties determine which strategy can deliver naturalistic feedback, and why ...
Sydney Swedick, Salim El Hadwe, Kesi Liang, George G. Malliaras, Damiano G. Barone   +4 more
wiley   +1 more source

A Novel Sleep Mechanism Inspired Continual Learning Algorithm

Guidance, Navigation and Control
Bayesian-based methods have emerged as an effective approach in continual learning (CL) to solve catastrophic forgetting. One prominent example is Variational Continual Learning (VCL), which demonstrates remarkable performance in task-incremental ...
Yuyang Han, Xiuxing Li, Tianyuan Jia, Qixin Wang, Chaoqiong Fan, Xia Wu   +5 more
doaj   +1 more source

Amyloid tracers detect multple binding sites in Alzheimer´s disease brain tissue. [PDF]

, 2013
Imaging fibrillar amyloid-β deposition in the human brain in vivo by positron emission tomography has improved our understanding of the time course of amyloid-β pathology in Alzheimer’s disease. The most widely used amyloid-β imaging tracer so far is 11C-
Nordberg, A,, Ni, Ruiqing, Marutle, Amelia, Gillberg, P-G, Marutle, A,, Bergfors, A, Nordberg, Agneta, Gillberg, Per-Göran, Bergfors, Assar, Ni, R,   +9 more
core   +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

The time lag in local field potential signals for the development of its Bayesian belief network

EURASIP Journal on Advances in Signal Processing
Purpose The objective is to suggest time as an important variable to consider in the network model, specifically when discussing causality. Methods There is a consideration of the context of functional connectivity because of the time importance of ...
Victor H. B. Tsukahara, Jordão N. O. Junior, Tamiris Prizon, Rafael N. Ruggiero, Carlos D. Maciel   +4 more
doaj   +1 more source