11 citations · 11 across the 6 of their papers we have counts for
6 papers
Adaptive Graph Normalized Sign Algorithm
Changran Peng, Yi Yan, Ercan E. Kuruoglu
Efficient and robust prediction of graph signals is challenging when the signals are under impulsive noise and have missing data. Exploiting graph signal processing (GSP) and lever…
Adaptive Least Mean pth Power Graph Neural Networks
Yi Yan, Changran Peng, Ercan E. Kuruoglu
In the presence of impulsive noise, and missing observations, accurate online prediction of time-varying graph signals poses a crucial challenge in numerous application domains. We…
Binarized Simplicial Convolutional Neural Networks
Yi Yan, Ercan E. Kuruoglu
Graph Neural Networks have a limitation of solely processing features on graph nodes, neglecting data on high-dimensional structures such as edges and triangles. Simplicial Convolu…
Adaptive Joint Estimation of Temporal Vertex and Edge Signals
Yi Yan, Tian Xie, Ercan E. Kuruoglu
The adaptive estimation of coexisting temporal vertex (node) and edge signals on graphs is a critical task when a change in edge signals influences the temporal dynamics of the ver…
Graph Normalized-LMP Algorithm for Signal Estimation Under Impulsive Noise
Yi Yan, Radwa Adel, Ercan Engin Kuruoglu
In this paper, we introduce an adaptive graph normalized least mean pth power (GNLMP) algorithm for graph signal processing (GSP) that utilizes GSP techniques, including bandlimite…
Adaptive Sign Algorithm for Graph Signal Processing
Yi Yan, Ercan E. Kuruoglu, Mustafa A. Altinkaya
Efficient and robust online processing technique of irregularly structured data is crucial in the current era of data abundance. In this paper, we propose a graph/network version o…