Results 241 to 250 of about 150,938 (302)

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Integrated spatio-temporal modeling with hybrid graph convolutions and the graph fourier neural operator for traffic prediction. [PDF]

Sci Rep
Hosseini SM, Rahmatinia SM, Hosseini-Seno SA.   +2 more
europepmc   +1 more source

Adaptive feature fusion network for machine fault diagnosis with multiple knowledge based graphs. [PDF]

Sci Rep
Liu C, Han J, Zhang Y, Zhang Z, Gao H, Jia L.   +5 more
europepmc   +1 more source

Hough's Transform-Based IoT Device for Automated Identification and Prediction of Blood Groups. [PDF]

J Biomed Phys Eng
Asokan V, Swamy VP, Baskaran S.
europepmc   +1 more source

Emotion Recognition Based on Fusion of Topological Features and Trajectory Images Derived from EEG Phase Space Reconstruction. [PDF]

Sensors (Basel)
Liang T, Zhu X, Song Y.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

A subspace method for space time adaptive processing

IEEE Transactions on Signal Processing, 2005
The problem of space-time adaptive processing (STAP) using a nonlinear array is considered. A key part of STAP is the estimation of the space-time covariance matrix of the received data. The conventional method of doing this causes significant performance degradation at short ranges because of the nonstationarity of the data.
openaire   +3 more sources

On Using a priori Knowledge in Space-Time Adaptive Processing

IEEE Transactions on Signal Processing, 2008
In space-time adaptive processing (STAP), the clutter covariance matrix is routinely estimated from secondary ldquotarget-freerdquo data. Because this type of data is, more often than not, rather scarce, the so-obtained estimates of the clutter covariance matrix are typically rather poor.
Petre Stoica, Jian Li 0001, Xumin Zhu, Joseph R. Guerci   +3 more
openaire   +3 more sources