paper-with-me

홈 › Papers

GSP = DSP + Boundary Conditions -- The Graph Signal Processing Companion Model

2023-03-04 · John Shi, Jose M. F. Moura

The paper presents the graph signal processing (GSP) companion model that naturally replicates the basic tenets of classical signal processing (DSP) for GSP. The companion model shows that GSP can be made equivalent to DSP 'plus' appropriate boundary conditions (bc) - this is shown under broad conditions and holds for arbitrary undirected or directed graphs. This equivalence suggests how to broaden GSP - extend naturally a DSP concept to the GSP companion model and then transfer it back to the common graph vertex and graph Fourier domains. The paper shows that GSP unrolls as two distinct models that coincide in DSP, the companion model based on (Hadamard or pointwise) powers of what we will introduce as the spectral frequency vector $\lambda$, and the traditional graph vertex model, based on the adjacency matrix and its eigenvectors. The paper expands GSP in several directions, including showing that convolution in the graph companion model can be achieved with the FFT and that GSP modulation with appropriate choice of carriers exhibits the DSP translation effect that enables multiplexing by modulation of graph signals.

📄 PDF Abstract BibTeX arXiv:2303.02480

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…

Similar Papers 제목 키워드 기반

The Companion Model -- a Canonical Model in Graph Signal Processing

2022-03-25 · John Shi, Jose M. F. Moura

This paper introduces a $\textit{canonical}$ graph signal model defined by a $\textit{canonical}$ graph and a $\textit{canonical}$ shift, the $\textit{companion}$ graph and the $\textit{companion}$ shift. These are canon…

model

Digraph Signal Processing with Generalized Boundary Conditions

2020-05-19 · Bastian Seifert, Markus Püschel

Signal processing on directed graphs (digraphs) is problematic, since the graph shift, and thus associated filters, are in general not diagonalizable. Furthermore, the Fourier transform in this case is now obtained from …

INTIMA: A Benchmark for Human-AI Companionship Behavior

2025-08-04 · Lucie-Aimée Kaffee, Giada Pistilli, Yacine Jernite arxiv

AI companionship, where users develop emotional bonds with AI systems, has emerged as a significant pattern with positive but also concerning implications. We introduce Interactions and Machine Attachment Benchmark (INTI…

Spectral Contraction of Boundary-Weighted Filters on delta-Hyperbolic Graphs

2025-06-18 · Le Vu Anh, Mehmet Dik, Nguyen Viet Anh

Hierarchical graphs often exhibit tree-like branching patterns, a structural property that challenges the design of traditional graph filters. We introduce a boundary-weighted operator that rescales each edge according t…

Not a Silver Bullet for Loneliness: How Attachment and Age Shape Intimacy with AI Companions

2026-02-12 · Raffaele Ciriello, Uri Gal, Ofir Turel arxiv

Artificial intelligence (AI) companions are increasingly promoted as solutions for loneliness, often overlooking how personal dispositions and life-stage conditions shape artificial intimacy. Because intimacy is a primar…

Causal Inference