Yun Lin

Application of Cloud Model in Rock Burst Prediction and Performance Comparison with Three Machine Learning Algorithms

2018 · IEEE Access

Rock burst is a common disaster in deep underground rock mass engineering excavation. In this paper, a cloud model (CM) is applied to classify and assess rock bursts. Some main factors that influence rock bursts …

Fast Encoding and Decoding Algorithms for Arbitrary $(n,k)$ Reed-Solomon Codes Over $\mathbb{F}_{2^m}$

2020 · IEEE Communications Letters

Recently, a new polynomial basis over finite fields was proposed such that the computational complexity of the fast Fourier transform (FFT) is O(n log n). Based on FFTs, the encoding and decoding algorithms for Reed-Solomon …

Multisignal Modulation Classification Using Sliding Window Detection and Complex Convolutional Network in Frequency Domain

2022 · IEEE Internet of Things Journal

With the development of the Internet of Things (IoT), the IoT devices are increasing day by day, resulting in increasingly scarce spectrum resources. At the same time, many IoT devices are facing inevitable malicious attacks. …

Ultra Lite Convolutional Neural Network for Fast Automatic Modulation Classification in Low-Resource Scenarios

2022 · arXiv (Cornell University)

Automatic modulation classification (AMC) is a key technique for designing non-cooperative communication systems, and deep learning (DL) is applied effectively to AMC for improving classification accuracy. However, most of the DL-based AMC methods have a …

A Novel Radio Frequency Fingerprint Identification Method Using Incremental Learning

2022 · 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)

Radio frequency fingerprint (RFF) is regarded as a key technology in physical layer security in various wireless communications systems. Deep learning (DL) has achieved great success in the field of signal identification, particularly in improving …

Few-Shot Domain Adaption-Based Specific Emitter Identification Under Varying Modulation

2023

Specific emitter identification (SEI) is an effective Internet of things (IoT) data flow protection technique of identifying individual emitters via unique characteristics of different emitters. However, deep learning-based methods are difficult to deal with the …

OATGA: Optimizing Adversarial Training via Genetic Algorithm for Automatic Modulation Classification

2023

Recently, with the explosive growth of the mobile devices, spectrum sensing for wireless devices has become an attractive research. Automatic modulation classification (AMC) is an important task in spectrum sensing and plays an important role …

Automated Similarity Metric Generation for Recommendation

2024 · arXiv (Cornell University)

The embedding-based architecture has become the dominant approach in modern recommender systems, mapping users and items into a compact vector space. It then employs predefined similarity metrics, such as the inner product, to calculate similarity …

A universal adversarial perturbations generation method based on feature aggregation

2024

Universal Adversarial Perturbations (UAP) is a sample-independent adversarial attack that can be added to all natural samples to change most of their predictive labels. Aiming at the problems of the existing universal adversarial attack methods …