Results 121 to 130 of about 1,081,536 (284)

Multiway Filtering Based on Fourth-Order Cumulants

EURASIP Journal on Advances in Signal Processing, 2005
We propose a new multiway filtering based on fourth-order cumulants for the denoising of noisy data tensor with correlated Gaussian noise. The classical multiway filtering is based on the TUCKALS3 algorithm that computes a lower-rank tensor ...
Muti Damien, Bourennane Salah
doaj   +1 more source

IF Estimation for Multicomponent Signals Using Image Processing Techniques in the Time-Frequency Domain [PDF]

, 2006
This paper presents a method for estimating the instantaneous frequency (IF) of multicomponent signals. The technique involves, firstly, the transformation of the one dimensional signal to the two dimensional time-frequency domain using a reduced ...
Boashash, B., Mesbah, M., Rankine, L.
core  

Phase Diagrams and Piezoelectric Properties of Wurtzite Al1−x−yScxGdyN Heterostructural Alloys

Advanced Science, EarlyView.
This study demonstrates ferroelectricity and piezoelectric properties improvement of quaternary wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films, guided by density functional theory calculations. Wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films have a high optical bandgap, enhanced piezoelectric ...
Julia L. Martin, Cheng‐Wei Lee, Nate S.P. Bernstein, Thi Nguyen, Ande Bryan, Eli Cooper, John S. Mangum, Sage R. Bauers, Andriy Zakutayev, Keisuke Yazawa, Prashun Gorai, Rebecca W. Smaha   +11 more
wiley   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

A Molecular Engineering Strategy to Fine‐Tune Phototoxicity of AIE Probes for Super‐Resolution Imaging of Mitochondrial Cristae Dynamics

Advanced Science, EarlyView.
Regulation of molecular packing, phototoxicity, and ROS output of AIE photosensitizers is achieved through carboxylation and alkyl‐chain‐length tuning. The probe designed via this strategy enables super‐resolution visualization of inner‐mitochondrial‐membrane cristae dynamics under controlled oxidative stress, and fluorescence‐lifetime imaging of ...
Kongqi Chen, Mengjie Wang, Chuen Kam, Zhiming Wang, Qinrong Zhang, Sijie Chen   +5 more
wiley   +1 more source

An Adaptive Quadratic Chirplet Transform Method

Nanjing Hangkong Hangtian Daxue Xuebao
Time‑frequency analysis becomes a powerful tool for processing nonstationary signals and is widely used in mechanical condition monitoring and system parameter identification under nonstationary operating conditions.
CHEN Jinke, SHI Zhiyu, PENG Xujun
doaj   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

TIME-FREQUENCY-BASED METHODS: APPLICATIONS TO SIGNAL ANALYSIS

Telemática, 2017
In communication systems it is of major importance the study of signals not only in time but also in the frequency domain. This is needed to characterize central frequency, bandwidth, channel effects or noise. This is useful to set properly transmitters
Jorge Torres Gómez
doaj  

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source