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20112023
most citedSynchronization of Memristive FitzHugh-Nagumo Neural Networks

16 citations · 31 across the 6 of their papers we have counts for

collaborators

6 papers

math.AP2023

Dynamics and Synchronization of Weakly Coupled Memristive Reaction-Diffusion Neural Networks

Yuncheng You, Junyi Tu

A new mathematical model of memristive neural networks described by the partly diffusive reaction-diffusion equations with weak synaptic coupling is proposed and investigated. Unde…

math.AP2023★ 16 cited

Synchronization of Memristive FitzHugh-Nagumo Neural Networks

Yuncheng You, Jing Tian, Junyi Tu

A new mathematical model of neural networks described by diffusive FitzHugh-Nagumo equations with memristors and linear synaptic coupling is proposed and investigated. The existenc…

cs.CG2019★ 7 cited

Propagate and Pair: A Single-Pass Approach to Critical Point Pairing in Reeb Graphs

Junyi Tu, Mustafa Hajij, Paul Rosen

With the popularization of Topological Data Analysis, the Reeb graph has found new applications as a summarization technique in the analysis and visualization of large and complex…

cs.GR2019

Topologically-Guided Color Image Enhancement

Junyi Tu, Paul Rosen

Enhancement is an important step in post-processing digital images for personal use, in medical imaging, and for object recognition. Most existing manual techniques rely on region…

cs.GR2018★ 2 cited

Inferring Quality in Point Cloud-based 3D Printed Objects using Topological Data Analysis

Paul Rosen, Mustafa Hajij, Junyi Tu +2

Assessing the quality of 3D printed models before they are printed remains a challeng- ing problem, particularly when considering point cloud-based models. This paper introduces an…

nlin.SI2011★ 6 cited

Explicit Flow Equations and Recursion Operator of the ncKP hierarchy

Jingsong He, Junyi Tu, Xiaodong Li +1

The explicit expression of the flow equations of the noncommutative Kadomtsev-Petviashvili(ncKP) hierarchy is derived. Compared with the flow equations of the KP hierarchy, our res…