-
Chapter and Conference Paper
SFRSwin: A Shallow Significant Feature Retention Swin Transformer for Fine-Grained Image Classification of Wildlife Species
Fine-grained image classification of wildlife species is a task of practical value and has an important role to play in the fields of endangered animal conservation, environmental protection and ecological con...
-
Chapter and Conference Paper
Intelligent Network Intrusion Detection and Situational Awareness for Cyber-Physical Systems in Smart Cities
Smart cities are enabled by cyber-physical systems (CPS) which leverage the Internet of Things (IoT) to connect the physical world and information systems. Due to lack of security protection, IoT systems are v...
-
Chapter and Conference Paper
Dual-Fisheye Image Stitching via Unsupervised Deep Learning
Constructing panoramic images from a dual-fisheye lens has been increasingly used along with the recent booming of new computer vision applications, such as virtual reality (VR) and augmented reality(AR). The ...
-
Chapter and Conference Paper
Phishing Frauds Detection Based on Graph Neural Network on Ethereum
Blockchain, as an emerging technology, has vulnerabilities that make the blockchain ecosystem rife with many criminal activities. However, existing technologies of phishing fraud detection heavily rely on shal...
-
Chapter and Conference Paper
Unsupervised Deep Learning-Based Hybrid Beamforming in Massive MISO Systems
Hybrid beamforming (HBF) is a promising approach for balancing the hardware cost, training overhead and system performance in massive MIMO systems. Optimizing the HBF through deep learning (DL) has gained cons...
-
Chapter and Conference Paper
A Deep Learning Based Intelligent Transceiver Structure for Multiuser MIMO
Precoding and post-processing are necessary technical steps for information recovery of multiple-input multiple-output (MIMO) systems, which can effectively suppress interference between data streams and impro...
-
Chapter and Conference Paper
Deep Learning-Based Power Control for Uplink Cognitive Radio Networks
In this paper, we study deep-learning-based power control methods for an underlay cognitive radio (CR) interference channel network, where the SUs are allowed to access the network on the promise of ensuring t...
-
Chapter and Conference Paper
Beamforming for MISO Cognitive Radio Networks Based on Successive Convex Approximation
This paper presents a novel beamforming optimization method for downlink underlying multiple-input single-output (MISO) cognitive radio (CR) networks. We formulate a beamforming optimization problem to maximiz...
-
Chapter and Conference Paper
Intelligent Dynamic Spectrum Access for Uplink Underlay Cognitive Radio Networks Based on Q-Learning
In this paper, the dynamic spectrum access (DSA) technique for an uplink underlay cognitive radio (CR) network is considered. The objective of the DSA scheme is to allow the secondary users (SUs) access the ne...
-
Article
On Analytical Achievable Rate for MIMO Linear Interference Alignment with Imperfect CSI
This paper studies the impact of channel error on the achievable rate of symmetrical K-user multiple-input multiple-output linear interference alignment (IA) networks. The upper and lower bounds of the achievable...
-
Chapter and Conference Paper
Adaptive Sub-Channel Allocation Based on Hopfield Neural Network for Multiuser OFDM
A kind of adaptive sub-channel allocation method utilizing Hopfield neural network (HNN) is studied in this paper. In order to find the power optimal sub-channel allocation under the constraints that only one ...
