Results 141 to 150 of about 5,787,304 (258)

New constant modulus algorithm suitable for nonconstant modulus signals

Tongxin xuebao, 2011
The steady-state mean square error（MSE） of constant modulus algorithm（CMA） can not converge to zero for nonconstant modulus signals.By changing the multimodulus of nonconstant modulus source to single modulus,a new cost function was defined.And the new ...
RAO Wei1, SUN Hui1, GUO Ye-cai2, DENG Cheng-zhi1, WANG Sheng-qian1, TIAN Wei1   +5 more
doaj  

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source

Comparative machine learning approach on Maxwell tetra hybrid nanofluid with porous and bioconvection over 3d rotating stretching sheet. [PDF]

Discov Nano
Soniya P, De P.
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Stratification in small randomised clinical trials and analysis of covariance: Some simple theory and recommendations. [PDF]

Stat Methods Med Res
Senn S, König F, Posch M.
europepmc   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

A mask-based peak-to-average power ratio reduction scheme for affine frequency division multiplexing systems using Volterra Series-Driven PolyNet. [PDF]

PLoS One
Liu X, Zhang Y, Guo J, Zhu R, Wang F, Wang L.   +5 more
europepmc   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source

Machine learning-based solar radiation prediction across heterogeneous climatic zones using NASA POWER data: a case study in Nigeria. [PDF]

Front Artif Intell
Faloye OT, Awotoye GT, Akinremi J, Olaleye OS, Oluwadare AO, Adeyeri OE, Laokhongthavorn L, Kamchoom V.   +7 more
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source