Results 141 to 150 of about 1,531 (279)

Design Optimization of Soft Fabric Pneumatic Actuators

Advanced Intelligent Systems, EarlyView.
This study presents a systematic optimization framework for elongating and bending fabric‐based soft pneumatic actuators. After a preliminary design‐space reduction, the framework minimizes energy consumption under mechanical performance constraints by integrating validated finite element modeling with statistical surrogate models. Optimal designs were
Grigorios M. Chatziathanasiou, Konstantina Tsintzira, Panagiotis Polygerinos   +2 more
wiley   +1 more source

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

Advanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen, Ali Çalhan, Murtaza Cicioğlu, Oğuzhan Demiryürek   +3 more
wiley   +1 more source

A Highly Efficient Compressive Sensing Algorithm Based on Root-Sparse Bayesian Learning for RFPA Radar

Remote Sensing
Off-grid issues and high computational complexity are two major challenges faced by sparse Bayesian learning (SBL)-based compressive sensing (CS) algorithms used for random frequency pulse interval agile (RFPA) radar.
Ju Wang, Bingqi Shan, Song Duan, Qin Zhang   +3 more
doaj   +1 more source

Energy‐Aware Perturbation Optimization for Memristor‐Array Convolutional Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristor‐array inference becomes more energy efficient when layer inputs are reshaped before computation. Sinusoidal perturbation encoding with dual‐threshold screening reduces active voltage pulses and contracts ADC input‐current ranges, jointly lowering crossbar and peripheral energy while preserving accuracy across hardware MNIST validation, deep ...
Ao Xu, Lun Lu, Youpeng Wu, Yao Guo, Yi Li, Yinan Wang, Qingjiang Li   +6 more
wiley   +1 more source

Bayesian Compressive Sensing Using Monte Carlo Methods

, 2013
Publication in the conference proceedings of EUSIPCO, Marrakech, Morocco ...
Ioannis Kyriakides, Radmila Pribic
openaire   +3 more sources

Playing in the Dark: Invisible Chess as a Laboratory for Strategic AI

AI &Innovation, EarlyView.
This paper shows that strategic AI evaluated on perfect‐information benchmarks can be brittle in real adversarial settings. By using invisible chess as a benchmark for hidden state and deception, it argues for stricter testing, human oversight, and more cautious governance of high‐stakes AI systems.
Paolo Ciancarini
wiley   +1 more source

Compressive Sensing Research Based on Bayesian Framework [PDF]

, 2011
压缩传感突破了奈奎斯特定理中要求采样率不小于最高频率两倍的瓶颈，在信号处理领域中具有广泛的应用前景。本文在学习压缩传感理论和重构算法后，对贝叶斯压缩传感算法进行了研究，主要完成工作如下： (1)针对许多重构算法逐行或逐列重构会割裂行列之间的相关性的问题，提出了两种改善方法，分别为基于行列最优图像重构和基于小波子带行列相关性图像重构。前者利用了小波子带系数的特征，后者利用了小波子带行列相关性的特征。与基于行列均衡图像重构的改善方法相比较，两种改善方法分别从性能和运行时间上有所改进。 (2 ...
蒋雯笑
core  

Preferential trading in agriculture: New insights from a structural gravity analysis and machine learning

American Journal of Agricultural Economics, EarlyView.
Abstract Preferential trade agreements (PTAs) contain various non‐tariff provisions, yet identifying their trade effects remains challenging because these commitments are high‐dimensional and strongly correlated within agreements. We estimated a theory‐consistent structural gravity model with domestic flows for 26 agricultural subsectors over 1988–2017
Dongin Kim, Sandro Steinbach
wiley   +1 more source

Reconstruction of 3D Objects in Anisotropic Multi-layered Media by a Bayesian Compressive Sensing Solver [PDF]

, 2015
International audienceThis paper investigates an innovative imaging approach for reconstructing 3D objects in complex anisotropic multi-layered media. A fast algorithm applied for solving the electromagnetic scattering problems in the anisotropic multi ...
Oliveri, Giacomo, Poli, Lorenzo, Ding, Ping-Ping, Massa, Andrea   +3 more
core   +2 more sources

Self‐Attention Mechanism Aided Bayesian Compressed Sensing for Distributed Compressive Sensing

Electronics Letters
ABSTRACT This letter addresses the joint sparse recovery (JSR) problem with multiple measurement vectors (MMV) in compressive sensing (CS). Be aware of the limitations of the model‐driven methods and the advantages of the latest data‐driven approaches; the authors transform the MMV problem into sequence modelling.
Feng Shu, Linghua Zhang, Qin Cheng
openaire   +1 more source