Results 61 to 70 of about 70,734 (340)

Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI [PDF]

IEEE Transactions on Image Processing, 2014
We develop a Bayesian nonparametric model for reconstructing magnetic resonance images (MRI) from highly undersampled k-space data. We perform dictionary learning as part of the image reconstruction process. To this end, we use the beta process as a nonparametric dictionary learning prior for representing an image patch as a sparse combination of ...
Huang, Yue, Paisley, John, Lin, Qin, Ding, Xinghao, Fu, Xueyang, Zhang, Xiao-Ping   +5 more
openaire   +4 more sources

Data‐Driven Discovery of Quaternary Ammonium Interlayers for Efficient and Thermally Stable Perovskite Solar Cells

Advanced Materials, EarlyView.
An active learning framework, grounded in independently generated in‐house experimental data, enables reliable discovery of high‐performance interfacial materials for perovskite solar cells. Iterative model refinement autonomously converges toward structurally robust quaternary ammonium architectures, establishing a new design principle for interfacial
Jongbeom Kim, Yang Jeong Park, Chaehoon Jeon, Nahye Shin, Jaewang Park, Seungun Lee, Jino Im, Sungroh Yoon, Sang Il Seok   +8 more
wiley   +1 more source

MT-BCS-Based DoA and Bandwidth Estimation of Unknown Signals through Multiple Snapshots Data

International Journal of Antennas and Propagation, 2020
The Direction-of-Arrival (DoA) and bandwidth (BW) estimation strategy impinging on a linear array using multiple snapshots data is addressed within the multitask Bayesian Compressive Sensing (MT-BCS).
Shi Hui Zhang, Qing He Zhang, Li Ping Shi, Chao Yi, Guang Xu Liu   +4 more
doaj   +1 more source

Two-Dimensional Pattern-Coupled Sparse Bayesian Learning via Generalized Approximate Message Passing

, 2015
We consider the problem of recovering two-dimensional (2-D) block-sparse signals with \emph{unknown} cluster patterns. Two-dimensional block-sparse patterns arise naturally in many practical applications such as foreground detection and inverse synthetic
Fang, Jun, Li, Hongbin, Zhang, Lizao
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

Magnetic Textiles: A Review of Materials, Fabrication, Properties, and Applications

Advanced Materials Technologies, EarlyView.
Magnetic textiles (M‐textiles) are emerging as a programmable materials platform that merges magnetic matter with hierarchical textile structures. This article consolidates magnetic material classes, textile architectures, and fabrication and magnetization strategies, revealing structure–property–function relationships that govern magneto‐mechanical ...
Li Ke, Moses Kumi, Xiaoming Tao, Junhong Pu   +3 more
wiley   +1 more source

WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing

Sensors, 2014
We address the problem of data acquisition in large distributed wireless sensor networks (WSNs). We propose a method for data acquisition using the hierarchical routing method and compressive sensing for WSNs. Only a few samples are needed to recover the
Zhiqiang Zou, Cunchen Hu, Fei Zhang, Hao Zhao, Shu Shen   +4 more
doaj   +1 more source

Hard‐Magnetic Soft Millirobots in Underactuated Systems

Advanced Robotics Research, EarlyView.
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang, Zixuan Zhang, Bingyan Li, Junkai Wang, Hongcheng Gu   +4 more
wiley   +1 more source

A Computerized Bioinspired Methodology for Lightweight and Reliable Neural Telemetry

Sensors, 2020
Personalized health monitoring of neural signals usually results in a very large dataset, the processing and transmission of which require considerable energy, storage, and processing time. We present bioinspired electroceptive compressive sensing (BeCoS)
Olufemi Adeluyi, Miguel A. Risco-Castillo, María Liz Crespo, Andres Cicuttin, Jeong-A Lee   +4 more
doaj   +1 more source

Adaptive Non-uniform Compressive Sampling for Time-varying Signals

, 2017
In this paper, adaptive non-uniform compressive sampling (ANCS) of time-varying signals, which are sparse in a proper basis, is introduced. ANCS employs the measurements of previous time steps to distribute the sensing energy among coefficients more ...
Joneidi, Mohsen, Rahnavard, Nazanin, Zaeemzadeh, Alireza   +2 more
core   +1 more source