Results 251 to 260 of about 1,005,453 (288)

Frequency domain iterative learning control for direct-drive robots

2003 European Control Conference (ECC), 2003
This paper presents an Iterative Learning Control algorithm for direct-drive robots. The learning algorithm assumes linear dynamics, which is created using a nonlinear model-based compensator. The convergence criterion of the learning controller is derived in the frequency domain.
Bukkems, B.H.M., Kostic, D., de Jager, Bram, Steinbuch, M.   +3 more
openaire   +3 more sources

Fast and Accurate Lane Detection via Frequency Domain Learning

Proceedings of the 29th ACM International Conference on Multimedia, 2021
It is desirable to maintain both high accuracy and runtime efficiency in lane detection. State-of-the-art methods mainly address the efficiency problem by direct compression of high-dimensional features. These methods usually suffer from information loss and cannot achieve satisfactory accuracy performance.
Yulin He, Wei Chen 0009, Zhengfa Liang, Dan Chen 0001, Yusong Tan, Xin Luo 0009, Chen Li 0034, Yulan Guo   +7 more
openaire   +1 more source

Deep learning network for NMR spectra reconstruction in time-frequency domain and quality assessment

Nature Communications
High-quality nuclear magnetic resonance (NMR) spectra can be rapidly acquired by combining non-uniform sampling techniques (NUS) with reconstruction algorithms.
Yao Luo, Wenhan Chen, Zhenhua Su, Xiaoqi Shi, Jie Luo, Xiaobo Qu, Zhong Chen, Yanqin Lin   +7 more
semanticscholar   +1 more source

Learning Frequency-Domain Fusion for Multimodal Remote Sensing Semantic Segmentation

IEEE Transactions on Geoscience and Remote Sensing
Multimodal remote sensing data substantially enhance semantic segmentation accuracy by providing complementary information across sensing modalities.
Guangsheng Chen, Fangyu Sun, Weipeng Jing, Weitao Zou, Donglin Di, Yang Song, Lei Fan   +6 more
semanticscholar   +1 more source

Transfer Learning Fourier Neural Operator for Solving Parametric Frequency-Domain Wave Equations

IEEE Transactions on Geoscience and Remote Sensing
Fourier neural operator (FNO) is a recently proposed data-driven scheme to approximate the implicit operators characterized by partial differential equations (PDEs) between functional spaces. The infinite-dimensional functional mapping from the parameter
Yufeng Wang, Hengran Zhang, Chen-Chih Lai, Xiangyun Hu   +3 more
semanticscholar   +1 more source

Contrastive Learning in Frequency Domain for Non-I.I.D. Image Classification

2021
Non-I.I.D. image classification is an important research topic for both academic and industrial communities. However, it is a very challenging task, as it violates the famous hypothesis of independent and identically distributed (I.I.D.) in conventional machine learning, and the classifier minimizing empirical errors on training images does not perform
Huan Shao 0005, Zhaoquan Yuan, Xiao Peng, Xiao Wu 0001   +3 more
openaire   +1 more source

A frequency domain iterative learning control for low bandwidth system

Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), 2001
A frequency-domain learning scheme based on the modified Fourier series for the tracking control of system with a low bandwidth limit is presented. The proposed controller consists of two parts: a PD controller, and an online updated learning controller. The proposed method can reduce the tracking error more effectively than the same type of controller
Wubi Qin, Lilong Cai
openaire   +1 more source

Adaptive Dual-Domain Learning for Hyperspectral Anomaly Detection With State-Space Models

IEEE Transactions on Geoscience and Remote Sensing
Recently, learning-based hyperspectral anomaly detection (HAD) methods have demonstrated outstanding performance, dominating mainstream research. However, the existing learning-based approaches still have two issues: 1) they rarely consider both the ...
Sitian Liu, Lintao Peng, Xuyang Chang, Zhen Wang, Guanghui Wen, Chunli Zhu   +5 more
semanticscholar   +1 more source

Learning in Time-Frequency Domain for Fractional Delay-Doppler Channel Estimation in OTFS

IEEE Wireless Communications Letters
In this letter, we propose a learning-based approach for estimation of fractional delay-Doppler (DD) channel in orthogonal time frequency space (OTFS) systems.
S. Mattu, A. Chockalingam
semanticscholar   +1 more source

CMMDL: Cross-modal multi-domain learning method for image fusion

Neural Networks
The rapid development of deep learning provides an excellent solution for end-to-end multi-modal image fusion. However, existing methods mainly focus on the spatial domain and fail to fully utilize valuable information in the frequency domain.
Di Yuan, Huayi Zhu, Rui Chen, Sida Zhou, Jianing Tang, Xiu Shu, Qiaojuan Liu   +6 more
semanticscholar   +1 more source