IEEE

When Knowledge Graph Meets Retrieval Augmented Generation for Wireless Networks: A Tutorial and Case Study

Abstract: This paper investigates a GraphRAG framework that integrates knowledge graphs into the Retrieval-Augmented Generation (RAG) architecture to enhance networking applications. While RAG has ...
IEEE

Discontinuous Dual-Signal PWM for Neutral-Point Voltage Balancing in Three-Level Converters

Abstract: Neutral-point voltage (NPV) imbalance presents a significant challenge in three-level converters, especially under conditions of high modulation index (MI) and low power factor (PF). This ...
IEEE

Quadratic Transform for Fractional Programming in Signal Processing and Machine Learning: A unified approach for solving optimization problems involving ratios

Abstract: Fractional programming (FP) is a branch of mathematical optimization that deals with the optimization of ratios. It is an invaluable tool for signal processing and machine learning, because ...
IEEE

Sleep EEG Signal Analysis using Graph Embedding Simplicial Convolutional Recurrent Attention Network with Duck Swarm Algorithm

Abstract: Sleep EEG Analysis (S-EEG-A) records brain activity to categorize sleep stages, identify patterns, and study disorders by frequency and waveform analysis. Sleep EEG signals are hard to ...
IEEE

A Radar Signal Open-Set Deinterleaving Method Based on Laplacian Pyramid Reconstruction and Adversarial Reciprocal Point Learning

Abstract: Radar signal deinterleaving is a challenging task in complex electromagnetic environments. This work proposes a method for accurately deinterleaving known and unknown radar radiation sources ...
IEEE

Dynamic Sensor Placement on Graphs Based on Graph Signal Sampling Theory

Abstract: In this paper, we consider a sensor placement problem where sensors can move within a network over time. Most existing methods assume that sensor positions are static, i.e., they do not move ...
IEEE

Rethinking Variational Bayes in Community Detection From Graph Signal Perspective

Abstract: Methods based on variational bayes theorytare widely used to detect community structures in networks. In recent years, many related methods have emerged that provide valuable insights into ...
IEEE

Enhancing EEG Motor Imagery Time Point Signal Classification through Reinforcement Learning and Graph Neural Networks

Abstract: Brain-Computer Interfaces (BCIs) rely on accurately decoding electroencephalography (EEG) motor imagery (MI) signals for effective device control. Graph Neural Networks (GNNs) outperform ...
IEEE

Petri net-based QUBO Model Formulation for Multi-Resource Flow-Shop Scheduling Problems

Abstract: This paper introduces a Petri net-based approach to addressing multi-resource flow-shop scheduling problems within multi-objective quantum optimization. The multi-resource flow-shop problem, ...
IEEE

Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow*

Abstract: Deep learning methods have recently shown significant promise in compressing the geometric features of point clouds. However, challenges arise when consecutive point clouds contain holes, ...
IEEE

Optimizing Access Point Placement in Industrial IoT: A Deep Reinforcement Learning Approach With Q-Learning Verification and Signal Heatmap Visualization

Abstract: Optimal access point (AP) placement inside an industrial layout is important to ensure excellent connectivity. However, wireless fidelity (Wi-Fi) AP placement is complicated because ...
Seeking Alpha

Sirius XM's Cash Flow Points To A Viable Contrarian Choice (Rating Upgrade)

Sirius XM is upgraded to a strong buy, offering deep value with a forward P/E of 6.65 and a 5.2% dividend yield. SIRI consistently beats earnings estimates, maintains stable revenue, and leverages ...