A5101830725- Complex Network Analysis Techniques
- Chaos control and synchronization
- Opinion Dynamics and Social Influence
- Chaos-based Image/Signal Encryption
- Advanced Adaptive Filtering Techniques
- Neural Networks and Applications
- Digital Filter Design and Implementation
- Face and Expression Recognition
- Complex Systems and Time Series Analysis
- Cellular Automata and Applications
- Blind Source Separation Techniques
- Fractal and DNA sequence analysis
- Image and Signal Denoising Methods
- Advanced MIMO Systems Optimization
- Advanced Steganography and Watermarking Techniques
- Full-Duplex Wireless Communications
- Heart Rate Variability and Autonomic Control
- Quantum chaos and dynamical systems
- RFID technology advancements
- Mathematical Dynamics and Fractals
- Advanced Wireless Communication Techniques
- Radar Systems and Signal Processing
- Advanced Electrical Measurement Techniques
- Digital Media Forensic Detection
- Advanced Data Compression Techniques
Southeast University
2015-2025
Shanghai Jiao Tong University
2020
Shanghai Ninth People's Hospital
2020
Southeast University
2007-2019
Institute of Electrical and Electronics Engineers
2018
Signal Processing (United States)
2018
Dalian Maritime University
2010
A complex-valued least-squares (CLS) framework is proposed in order to enhance the accuracy of smart discrete Fourier transform (SDFT) algorithms for power system frequency estimation presence noise and harmonic pollution. It first established that underlying time-series relationship among consecutive DFT fundamental components employed by original SDFT does not hold when noises or unexpected higher harmonics are present, resulting suboptimal performances. To eliminate these adverse effects...
In future full-duplex communications, the cancellation of self-interference (SI) arising from hardware nonidealities will play an important role in design mobile-scale devices. To this end, we introduce optimal digital SI solution for shared-antenna-based direct-conversion transceivers. establish that underlying widely linear signal model is not adequate strong transmit signals, impact various circuit imperfections, including power amplifier distortion, frequency-dependent I/Q imbalance,...
In future high-speed communication networks, the in-phase/quadrature (I/Q) imbalance mitigation and oscillator drift compensation is a key issue in design of orthogonal frequency division multiplexing (OFDM)-based wireless LAN (WLAN) transmitters. To this end, we propose two-stage I/Q measurement method, where by virtue WLAN standard-compliant training sequences, coarse estimation initially performed jointly with channel equalization. This makes it possible to decouple effects...
Along with current multi-scale based detectors, Feature Aggregation and Enhancement (FAE) modules have shown superior performance gains for cutting-edge object detection. However, these hand-crafted FAE show inconsistent improvements on face detection, which is mainly due to the significant distribution difference between its training applying corpus, COCO vs. WIDER Face. To tackle this problem, we essentially analyse effect of data distribution, consequently propose search an effective...
Evolutionary programming has been applied to many optimization problems. However, on some function problems its convergence rate is slow. In this paper, swarm directions are embedded in fast evolutionary programming. The direction for an individual supplies place be mutated. experimental results show effectiveness and efficiency.
In a multi-tag radio frequency identification (RFID) system, signals sent from different tags are likely to interfere with others, leading degradation in the transmission quality. To solve this problem, novel widely linear minimum-mean-square-error (WLMMSE) anti-collision method is proposed by taking into account improper second-order statistics of backscattered tag signals, which result quadrature nature RFID readers. The provides an efficient means separate multiple overlapping within...
Empirical mode decomposition (EMD) is a fully data-driven technique designed for multi-scale of signals into their natural scale components, called intrinsic functions (IMFs). When EMD directly applied to perform fusion multivariate data from multiple and heterogeneous sources, the problem uniqueness, that is, different numbers levels likely occur, due empirical nature EMD. Although (MEMD) has been proposed temporal data, which employs real-valued projections along directions on unit...
In this paper, we extend symbolic dynamics, a standard analytical method for 1-D chaotic map, and initiate solution to the problem of estimation in coupled map lattices (CMLs) by introducing vector dynamics. We develop novel technique estimating initial conditions. also expand applicable scope word-lifting parameter from CMLs. Both theoretical experimental results show that those algorithms can construct one-to-one correspondence between set global orbits admissible codes. Therefore, provide...
Novel physical insights are provided into the mean square performance bounds of quaternion-valued widely linear (WL), semi-widely (SWL), and strictly estimators for generality Gaussian data. This is achieved by first defining three kinds complementary errors (CMSEs) these further exploiting corresponding degrees 'Hi-improperness (second-order noncircularity). Next, investigation attainable CMSEs classes shows that only a joint consideration proposed CMSE analysis standard MSE provides enough...
This paper presents a new routing strategy by introducing tunable parameter into the minimum information path we proposed previously. It is found that network transmission capacity can be considerably enhanced adjusting with various allocations of node capability for packet delivery. Moreover, provides traffic load distribution which better match allocation than traditional efficient strategies, leading to improved performance. strategy, without deviating from shortest-path in length paths...
A full performance analysis of the widely linear (WL) minimum variance distortionless response (MVDR) beamformer is introduced. While WL MVDR known to outperform its strictly counterpart, Capon beamformer, for noncircular complex signals, existing approaches provide limited physical insights, since they explicitly or implicitly omit complementary second-order (SO) statistics output interferences and noise (IN). To this end, we exploit SO IN introduce a framework beamformer. This makes it...