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20212025
most citedMultichannel Orthogonal Transform-Based Perceptron Layers for Efficient ResNets

7 citations · 29 across the 22 of their papers we have counts for

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6 papers · 1 filter

eess.SP2025

Edge-Fog Computing-Enabled EEG Data Compression via Asymmetrical Variational Discrete Cosine Transform Network

Xin Zhu, Hongyi Pan, Ahmet Enis Cetin

The large volume of electroencephalograph (EEG) data produced by brain-computer interface (BCI) systems presents challenges for rapid transmission over bandwidth-limited channels i…

eess.SP2023★ 1 cited

Electroencephalogram Sensor Data Compression Using An Asymmetrical Sparse Autoencoder With A Discrete Cosine Transform Layer

Xin Zhu, Hongyi Pan, Shuaiang Rong +1

Electroencephalogram (EEG) data compression is necessary for wireless recording applications to reduce the amount of data that needs to be transmitted. In this paper, an asymmetric…

eess.SP2023

Stein Variational Gradient Descent-based Detection For Random Access With Preambles In MTC

Xin Zhu, Hongyi Pan, Salih Atici +1

Traditional preamble detection algorithms have low accuracy in the grant-based random access scheme in massive machine-type communication (mMTC). We present a novel preamble detect…

eess.SP2022★ 1 cited

Real-time Wireless ECG-derived Respiration Rate Estimation Using an Autoencoder with a DCT Layer

Hongyi Pan, Xin Zhu, Zhilu Ye +2

In this paper, we present a wireless ECG-derived Respiration Rate (RR) estimation using an autoencoder with a DCT Layer. The wireless wearable system records the ECG data of the su…

eess.SP2022★ 1 cited

Detecting Anomaly in Chemical Sensors via L1-Kernels based Principal Component Analysis

Hongyi Pan, Diaa Badawi, Ishaan Bassi +2

We propose a kernel-PCA based method to detect anomaly in chemical sensors. We use temporal signals produced by chemical sensors to form vectors to perform the Principal Component…

eess.SP2021

Multiplication-Avoiding Variant of Power Iteration with Applications

Hongyi Pan, Diaa Badawi, Runxuan Miao +2

Power iteration is a fundamental algorithm in data analysis. It extracts the eigenvector corresponding to the largest eigenvalue of a given matrix. Applications include ranking alg…