Suchergebnisse - "Signal processing algorithms"

Robust Aggregation for Federated Learning von Pillutla, Krishna, Kakade, Sham M., Harchaoui, Zaid

“… We present a novel approach to federated learning that endows its aggregation process with greater robustness to potential poisoning of local data or model …”
Volltext

Learning to Detect von Samuel, Neev, Diskin, Tzvi, Wiesel, Ami

“… In this paper, we consider multiple-input-multiple-output detection using deep neural networks. We introduce two different deep architectures: a standard fully …”
Volltext

Model-Based Deep Learning von Shlezinger, Nir, Whang, Jay, Eldar, Yonina C., Dimakis, Alexandros G.

“… Signal processing, communications, and control have traditionally relied on classical statistical modeling techniques. Such model-based methods utilize …”
Volltext

Sparse Regularization via Convex Analysis von Selesnick, Ivan

“… Sparse approximate solutions to linear equations are classically obtained via L1 norm regularized least squares, but this method often underestimates the true …”
Volltext

Toward Dual-functional Radar-Communication Systems: Optimal Waveform Design von Liu, Fan, Zhou, Longfei, Masouros, Christos, Li, Ang, Luo, Wu, Petropulu, Athina

“… We focus on a dual-functional multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single transmitter with multiple antennas …”
Volltext

Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview von Yuejie Chi, Lu, Yue M., Yuxin Chen

“… Substantial progress has been made recently on developing provably accurate and efficient algorithms for low-rank matrix factorization via nonconvex …”
Volltext

Fairness for Non-Orthogonal Multiple Access in 5G Systems von Timotheou, Stelios, Krikidis, Ioannis

“… In non-orthogonal multiple access (NOMA) downlink, multiple data flows are superimposed in the power domain and user decoding is based on successive …”
Volltext

Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning von Ying Sun, Babu, Prabhu, Palomar, Daniel P.

“… This paper gives an overview of the majorization-minimization (MM) algorithmic framework, which can provide guidance in deriving problem-driven algorithms with …”
Volltext

Channel Estimation for RIS Assisted Wireless Communications-Part II: An Improved Solution Based on Double-Structured Sparsity von Wei, Xiuhong, Shen, Decai, Dai, Linglong

“… Reconfigurable intelligent surface (RIS) can manipulate the wireless communication environment by controlling the coefficients of RIS elements. However, due to …”
Volltext

FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data von Zhang, Xinwei, Hong, Mingyi, Dhople, Sairaj, Yin, Wotao, Liu, Yang

“… Federated Learning (FL) is popular for communication-efficient learning from distributed data. To utilize data at different clients without moving them to the …”
Volltext

Sparse Activity Detection for Massive Connectivity von Chen, Zhilin, Sohrabi, Foad, Yu, Wei

“… This paper considers the massive connectivity application in which a large number of devices communicate with a base-station (BS) in a sporadic fashion. Device …”
Volltext

Learning Laplacian Matrix in Smooth Graph Signal Representations von Xiaowen Dong, Thanou, Dorina, Frossard, Pascal, Vandergheynst, Pierre

“… The construction of a meaningful graph plays a crucial role in the success of many graph-based representations and algorithms for handling structured data, …”
Volltext

AMP-Inspired Deep Networks for Sparse Linear Inverse Problems von Borgerding, Mark, Schniter, Philip, Rangan, Sundeep

“… Deep learning has gained great popularity due to its widespread success on many inference problems. We consider the application of deep learning to the sparse …”
Volltext

Channel Estimation for RIS Assisted Wireless Communications-Part I: Fundamentals, Solutions, and Future Opportunities von Wei, Xiuhong, Shen, Decai, Dai, Linglong

“… The reconfigurable intelligent surface (RIS) with low hardware cost and energy consumption has been recognized as a potential technique for future 6G …”
Volltext

Penalty Dual Decomposition Method for Nonsmooth Nonconvex Optimization-Part I: Algorithms and Convergence Analysis von Shi, Qingjiang, Hong, Mingyi

“… Many contemporary signal processing, machine learning and wireless communication applications can be formulated as nonconvex nonsmooth optimization problems …”
Volltext

Channel Estimation in Broadband Millimeter Wave MIMO Systems With Few-Bit ADCs von Mo, Jianhua, Schniter, Philip, Heath, Robert W.

“… We develop a broadband channel estimation algorithm for millimeter wave (mmWave) multiple input multiple output (MIMO) systems with few-bit analog-to-digital …”
Volltext

Image Fusion With Convolutional Sparse Representation von Liu, Yu, Chen, Xun, Ward, Rabab K., Jane Wang, Z.

“… As a popular signal modeling technique, sparse representation (SR) has achieved great success in image fusion over the last few years with a number of …”
Volltext

Generalized Correntropy for Robust Adaptive Filtering von Badong Chen, Lei Xing, Haiquan Zhao, Nanning Zheng, Principe, Jose C.

“… As a robust nonlinear similarity measure in kernel space, correntropy has received increasing attention in domains of machine learning and signal processing …”
Volltext

An Efficient Implementation of the Generalized Labeled Multi-Bernoulli Filter von Vo, Ba-Ngu, Vo, Ba-Tuong, Hoang, Hung Gia

“… This paper proposes an efficient implementation of the generalized labeled multi-Bernoulli (GLMB) filter by combining the prediction and update into a single …”
Volltext

Learning to Optimize: Training Deep Neural Networks for Interference Management von Sun, Haoran, Chen, Xiangyi, Shi, Qingjiang, Hong, Mingyi, Fu, Xiao, Sidiropoulos, Nicholas D.

“… Numerical optimization has played a central role in addressing key signal processing (SP) problems. Highly effective methods have been developed for a large …”
Volltext