Ciochina, "On Regularization in Adaptive Filtering," IEEE Transactions on Audio, Speech, and Language Processing, vol. 19, no. 6, pp. 1734-1742, 2011.On Regularization in Adaptive Filtering. J Benesty,C Paleolog
This paper provides a historical overview of adaptive-filter theory spanning the past 50 years. In Section2, we review the problems of filters including filtered errors as they emerged in the 1970s. In Section3, we formally introduce the two different concepts of stability, MSE, andl2−stabil...
Regularization: in our composite layer, the spatial and semantic functions are defined by two separate weight tensors, which are then multiplied to obtain a unique weight tensor whose rank is constrained to be lower or equal to that of the smaller factor. This low-rank property can be consider...
Such a quadratic error measure has also been employed in adaptive-filter theory as a practical means to derive convergence in the mean-square sense, starting with Ungerböck in 1972 [2] who applied the technique onto Widrow and Hoff’s famous least-mean-square (LMS) algorithm [3]1. He a...
HybridCR: Weakly-Supervised 3D Point Cloud Semantic Segmentation via Hybrid Contrastive Regularization 3D视觉工坊 2023/04/29 6250 Github项目推荐 | Awesome-Image-Inpainting 图像补全相关资源大列表 编程算法 [1] Bertalmio, M., Sapiro, G., Caselles, V., & Ballester, C. (2000, July). Image inpain...
and\(\bar {\gamma } \in \mathbb {R}_{+}\)is the upper bound for the magnitude of the error signal that is acceptable and it is usually chosen as a multiple of the noise standard deviationσn[2,10]. The parameter\(\delta \in \mathbb {R}_{+}\)is a regularization factor, gener...
CFAR Detection Based on the Nonlocal Low-Rank and Sparsity-Driven Laplacian Regularization for HFSWR. Xinyang Wang Yang Li Ning Zhang Qingxiang Zhang 原文链接 谷歌学术 必应学术 百度学术 Low-Complexity Blind Equalization in Q/V Band Satellite Links: An Experimental Assessment. Tommaso Rossi Mau...
Scalable Penalized Regression for Noise Detection in Learning with Noisy Labels Yikai Wang, Xinwei Sun, Yanwei Fu 2022 Confidence Adaptive Regularization for Deep Learning with Noisy Labels Yangdi Lu, Yang Bo, Wenbo He 2021 Data fusing and joint training for learni...
2024, Shiyou Diqiu Wuli Kantan/Oil Geophysical Prospecting Prestack sparse envelope seismic inversion method adopting the L<inf>0</inf> - L<inf>2</inf> -norm regularization 2024, Interpretation View all citing articles on ScopusView Abstract ...
a novel in-depth analysis of the computational complexity of the previously proposed SA filtering concepts is provided and contrasted with the computational complexity of the novel ESA filtering concept, adaptive HGMs, and conventional adaptive linear filters. Beyond previous investigations [22], this ar...