Xinshan Zhu

Tianjin University | tju · School of Electrical Engineering and Automation

Three phase PWM rectifiers have excellent performance when the grid voltages are balanced, and it is widely adopted in the industry. However, the asymmetrical loads or grid faults will lead to the unbalanced grid voltages. In addition, the negative sequence (NS) voltages and currents in the unbalanced grid result in the fluctuation of the DC bus vo...

For an electric vehicle charging system, its control performance and reliability are affected by the health and aging of dc bus capacitor in the three-phase pulsewidth modulation (PWM) rectifier. To monitor the status of capacitor and then adjust the operation mode in time, a dc bus capacitance identification method based on the frequency domain da...

The estimation of the state of health (SOH) of lithium-ion batteries (LIBs) plays an important role in ensuring the safe and stable operation of LIB management systems. In order to more accurately predict SOH, a model based on a sparse self-attentive transformer (SSAT) with multitimescale feature fusion is proposed. The SSAT follows an encoder-deco...

In order to improve the control performance and reliability of the pulse-width modulation (PWM) rectifiers in electric vehicle (EV) charging systems, the evaluation of DC bus capacitor health status is critical. In order to accurately monitor the health status of DC bus capacitors, a data-driven model fusion method is developed. In the method, mult...

The rapid development of digital image inpainting technology is causing serious hidden danger to the security of multimedia information. In this paper, a deep network called frequency attention-based dual-stream network (FADS-Net) is proposed for locating the inpainting region. FADS-Net is established by a dual-stream encoder and an attention-based...

In order to improve the performance and reliability of the three-phase PWM rectifier in electric vehicle (EV) charging system, it is important to focus on the identification of the DC bus capacitance. The existing methods have the disadvantages such as a low identification accuracy, a high hardware dependency, and high costs. Therefore, the develop...

In three-phase PWM rectifiers, the variation of the DC side load may be frequent and violent, and the DC bus voltage is prone to oscillate greatly. While the dynamic response and the steady-state characteristics of the DC bus voltage are important to the DC bus side load of PWM rectifiers. Therefore, it is necessary to improve the anti-load disturb...

Under the condition of the unbalanced grid, the second-order harmonic voltage ripple exists on the dc bus of the three-phase PWM rectifier. In this article, the internal relationship between the dc bus voltage ripple and the dc bus impedance is revealed. In addition, this article proposes a voltage ripple suppression method free from the power mode...

As an advanced image editing technology, image inpainting leaves very weak traces in the tampered image, causing serious security issues, particularly those based on deep learning. In this paper, we propose the global–local feature fusion network (GLFFNet) to locate the image regions tampered by inpainting based on deep learning. GLFFNet consists o...

Critical transmission ranges (or radii) in wireless ad-hoc and sensor networks have been extensively investigated for various performance metrics such as connectivity, coverage, power assignment and energy consumption. However, the regions on which the networks are distributed are typically either squares or disks in existing works, which seriously...

This paper presents a topology of integrated on-board charging system with separated inductors on grid side. It employs the on-board three-phase electric power converter in time-division multiplexing, and separates the grid side inductors from the vehicle, reducing volume, weight and cost of the on-board charging system. To provide an accurate indu...

The ac side structure of a bridgeless single-stage isolated ac–dc converter reduces the number of components by sharing power switches between the bridgeless rectifier and the dual-active-bridge (DAB) dc–dc converter. However, it also makes it more difficult to achieve zero-voltage switching (ZVS) for the ac side switches. Therefore, a modulation s...

Integrated energy systems (IES) with cooling, heat, electricity, and natural gas have drawn significant interest recently as we embrace more sustainable energy a midst climate change. However, the uncertain outputs of distributed generators (DGs) make it challenging for IES planning while maintaining low-cost installation and operation under carbon...

At different times, the load correlation of the integrated energy system (IES) is different and its changes over time are regular. However, the regularity of such changes is rarely considered in the current IES prediction research. In view of the above reasons, an IES short‐term load forecasting method based on load‐correlation peaks and valleys is...

The Electroencephalogram (EEG) signal, as a data carrier that can contain a large amount of information about the human brain in different states, is one of the most widely used metrics for assessing human psychophysiological states. Among a variety of analysis methods, deep learning, especially convolutional neural network (CNN), has achieved rema...

Single image dehazing is an important but challenging computer vision problem. For the problem, an end-to-end convolutional neural network, named multi-stream fusion network (MSFNet), is proposed in this paper. MSFNet is built following the encoder-decoder network structure. The encoder is a three-stream network to produce features at three resolut...

This paper presents a non-singular terminal sliding mode control (NTSMC) design based on an improved extended state observer (IESO) with application to an omnidirectional mobile manipulator (OMM) for trajectory tracking control. Firstly, a unified dynamic model is derived based on Lagrange method for an OMM prototype. An IESO that can reduce the in...

Background The genomics data analysis has been widely used to study disease genes and drug targets. However, the existence of missing values in genomics datasets poses a significant problem, which severely hinders the use of genomics data. Current imputation methods based on a single learner often explores less known genomic data information for im...

Energy consumption is an important issue for resource-constrained wireless neural recording applications with limited data bandwidth. Compressed sensing (CS) is a promising framework for addressing this challenge because it can compress data in an energy-efficient way. Recent work has shown that deep neural networks (DNNs) can serve as valuable mod...

Current ripples produced in single-phase onboard charging systems of electric vehicles (EVs) impact the lifetime of their batteries. In this paper, an isolated multi-functional charger topology is proposed. The charging system can be used to charge the auxiliary batteries or serve as an active filter (AF) for the power battery charger. By time-shar...

Although high dynamic range (HDR) is now a common format of digital images, limited work has been done for HDR source forensics. This paper presents a method based on a convolutional neural network (CNN) to detect the source of HDR images, which is built in the discrete cosine transform (DCT) domain. Specifically, the input spatial image is convert...

This paper investigates the problem of precise trajectory tracking control of an autonomous underwater vehicle (AUV) under parameter perturbations and external disturbances. To design a data-driven control scheme with high tracking accuracy and strong robustness, a compensated model-free adaptive control (MFAC) scheme is proposed by combining an ex...

The existing face image completion approaches cannot be utilized to rationally complete damaged face images where their identity information is completely lost due to being obscured by center masks. Hence, in this paper, a reference-guided double-pipeline face image completion network (RG-DP-FICN) is designed within the framework of the generative...

High voltage direct current (HVDC) is expected to bring forth large capacity, long transmission distance, and asynchronous grid interconnection. To quantitatively analyze the protection systems of HVDC, an evaluation system is proposed with a novel indicator framework and an innovative weighting method for the assessment of HVDC operating status. T...

Many forensic techniques have recently been developed to determine whether an image has undergone a specific manipulation operation. When multiple consecutive operations are applied to images, forensic analysts not only need to identify the existence of each manipulation operation, but also to distinguish the order of the involved operations. Howev...

This paper presents a novel median filtering forensics approach, based on a convolutional neural network (CNN) with an adaptive filtering layer (AFL), which is built in the discrete cosine transform (DCT) domain. Using the proposed AFL, the CNN can determine the main frequency range closely related with the operational traces. Then, to automaticall...

This paper presents an output feedback tracking control scheme for a three-wheeled omnidirectional mobile robot, based on passivity property and a modified generalized proportional integral (GPI) observer. The proposed control approach is attractive from an implementation point of view, since only one robot geometrical parameter (i.e., contact radi...

The transient output prediction of photovoltaic power supply is of great significance for power grid stability analysis, power quality control and fault diagnosis. For this reason, this paper first establishes the discretization model and linear prediction model of ideal photovoltaic power supply. Then, the parameters of the power supply model are...

This paper presents an extended state observer (ESO) based robust friction compensation scheme for trajectory tracking control of a three-wheeled omnidirectional mobile robot. The proposed approach is practical in implementation, with no friction model required and only three parameters to be tuned. First, a dynamic model with unknown friction forc...

The back-propagation neural network (BPNN) is a well-known multi-layer feed-forward neural network which is trained by the error reverse propagation algorithm. It is very suitable for the complex of short-term traffic flow forecasting; however, BPNN is easy to fall into local optimum and slow convergence. In order to overcome these deficiencies, a...

State equations are usually used for structural or qualitative analysis, such as deadlock checking, in P/T systems. In this paper, we instead consider timed state equations in stochastic process algebra models, to derive quantified dynamic information on the system modelled in the face of the state space explosion problem. The average of these stat...

A novel image inpainting forensics algorithm based on the deep neural network is proposed, in which the vestigial features can be automatically extracted by the encoder network, the category of each pixel is predicted by the decoder network, and thus whether or not the image is with inpainting and falsification as well as the inpainted and falsifie...

With the advent of the Internet of Things (IoT) as a major force of change in industry, Cyber Physical Systems (CPS) is right for building the concept smart Environment. In CPS, the internal computational and physical elements generally interact, reflect and influence each other in order to obtain and analyze human behaviors and their social activi...

Although image inpainting is now an effective image editing technique, limited work has been done for inpainting forensics. The main drawbacks of the conventional inpainting forensics methods lie in the difficulties on inpainting feature extraction and the very high computational cost. In this paper, we propose a novel approach based on a convoluti...

Image quality assessment is a basic problem in the multimedia field. A new image quality metric is constructed based on Structural Similarity (SSIM) index, by exploiting Human Visual System (HVS) characteristics. First, considering the masking effects of HVS, the distorted image is preprocessed by a distortion model with the input of the error betw...

Conventional electronic noses need complicated data preprocessing and tedious feature reduction steps for different sensors and applications. To overcome the drawbacks, a bio-inspired data processing method using spike-based olfactory model is proposed in this paper, which consists of spike encoding by virtual olfactory receptor neurons (VORNs) and...

Objective: Data compression is crucial for resource-constrained wireless neural recording applications with limited data bandwidth, and Compressed Sensing (CS) theory has successfully demonstrated its potential in neural recording applications. In this paper, an analytical, training-free CS recovery method, termed Group Weighted Analysis l1-Minimi...

k-NN (k Nearest Neighbour) density estimate as a nonparametric estimation method is widely used in machine learning or data analysis. The convergence problem of k-NN approach has been intensively investigated. In particular, the equivalence of convergence in weak or strong sense (i.e. in probability sense or in almost surely sense) has been respect...

In low-power wireless neural recording tasks, signals must be compressed before transmission to extend battery life. Recently, Compressed Sensing (CS) theory has successfully demonstrated its potential in neural recording applications. In this study, a deep learning framework of quantized CS, termed BW-NQ-DNN, is proposed, which consists of a binar...

This paper presents an optimal watermark embedding method combining spread spectrum and quantization. In the method, the host signal vector is quantized to embed a multiple-bit watermark, and meanwhile, the quantized signal is made to locate in the detectable region defined in the context of spread spectrum watermarking. Under the two constraints,...

In this paper, the problem of altitude and attitude control for a quadrotor with model parametric uncertainties and external disturbance is studied. In order to improve system robustness and dynamic response, a novel linear active disturbance rejection sliding mode controller is designed. The basic idea is to estimate the uncertainties and disturba...

An analytical model has been developed in the present paper based on a square root transformation of white Gaussian noise. The mathematical expectation and variance of the new asymmetric distribution generated by white Gaussian noise after a square root transformation are analytically deduced from the preceding four terms of the Taylor expansion. T...

Reliable and energy-efficient wireless data transmission remains a major challenge in resource-constrained wireless neural recording tasks, where data compression is generally adopted to relax the burdens on the wireless data link. Recently, Compressed Sensing (CS) theory has successfully demonstrated its potential in neural recording application....

It is, as the state space explosion problem indicates, not uncommon that tremendous complexity and size of a system would annoyingly quiver the performance of discrete state-based modeling formalisms. The past few years, however, have inspiringly witnessed a brand new PEPA-based strategy offering a feasible solution against such disturbing puzzle....

Infrastructure as a service (IaaS) is a form of cloud computing, which converts physical machines (PMs) to various types of resources by virtualization technology, and delivers these resources to customers by a on-demand way. However, different customer requirements complicate the usage of resources. In this paper, we employ a high level formalizat...

The goal of photo aesthetics assessment is to build a computational model which can estimate the aesthetics quality of digital images with respect to human׳s perception. As one of the most important features that determine the degree of image׳s aesthetics quality, color harmony has gained increasing attentions. To overcome the problems of most clas...

A novel quantization watermarking method is presented in this paper, which is developed following the established feature modulation watermarking model. In this method, a feature signal is obtained by computing the normalized correlation (NC) between the host signal and a random signal. Information modulation is carried out on the generated NC by s...

This paper, based on $k$-NN graph, presents symmetric $(k,j)$-NN graph $(1 \leq j < k)$, a brand new topology which could be adopted by a series of network-based structures. We show that the $k$ nearest neighbors of a node exert disparate influence on guaranteeing network connectivity, and connections with the farthest $j$ ones among these $k$ neig...

This paper presents a double domain watermarking (DDW) method for binary document image. In this method, the watermark patterns are generated as signals in the discrete cosine transform (DCT) domain, and modulated with the embedded message. The modulated signal is then transformed into the spatial domain and adapted to the characteristics of human...

To effectively retrieve objects from large corpus with high accuracy is a challenge task. In this paper, we propose a method that propagates visual feature level similarities on a Markov random field (MRF) to obtain a high level correspondence in image space for image pairs. The proposed correspondence between image pair reflects not only the simil...

The first goal of this article is to analyze the performance of dither modulation (DM) against the composite attacks including valumetric scaling, additive noise and constant change. The analyzes are developed under the assumptions that the host vector and noise vector are mutually independent and both of them have independently and identically dis...

This paper presents a fluid approximation approach which is associated with the high-level system description and modelling formalism PEPA, to model and evaluate large scale content adaptation systems. This approach can achieve high accuracy at a low computational cost, so it can avoid the state-space explosion problem which results in the difficul...

This paper presents a novel quantization-based watermarking method. The method embeds the watermark information by modulating a feature signal generated from the host signal. The feature signal is suggested to choose the normalized correlation between the host signal and a random signal. Information modulation is carried out on the generated featur...

This paper presents a novel quantization based watermarking scheme. Watermark embedding is performed through modulating the normalized correlation between the host vector and a random vector with dither modulation. The watermarked signal is derived to provide the modulated normalized correlation in the sense of minimizing the embedding distortion....

In this paper, we analyze the performance of dither modulation (DM) against the composite attacks including valumetric scaling, additive noise and constant change. The analyses are developed under the assumptions that the host vector and noise vector are mutually independent and both of them have independently and identically distributed components...

This paper presents a double domain watermarking scheme for binary document image. The watermark patterns are generated as the discrete cosine transform (DCT) domain signals, and then perceptually shaped through weighting its components in the spatial domain with the perceptual masks. The perceptual masks are obtained by applying a psychovisual mod...

This paper presents a novel quantization based watermarking scheme. Watermark embedding is performed through modulating the angle between the host vector and a random vector with dither modulation technique. The watermarked signal with the modulated angle is derived in the sense of minimizing the embedding distortion. The proposed scheme is theoret...

In this paper, we analyze the performance of dither modulation (DM) against the composite attacks including valumetric scaling, additive noise and constant change. The analyses are developed under the assumptions that the host vector and noise vector are mutually independent and both of them have independently and identically distributed components...

In the last decade, the requirement for copyright protection of digital multimedia has become more and more urgent. As an efficient method to address this issue, watermarking has gained a lot of attention. To watermarking system, detectors have an important influence on its performance. In this paper, we propose a new optimal detector to multiplica...

This paper presents a novel image watermarking approach in the framework of double domain watermarking. The watermark pattern is generated as a discrete cosine transform domain signal, and adapted to the characteristics of human visual system by adjusting the localized embedding strength in the spatial domain. Watermark detection can be operated ap...

This paper develops a new mask in the spatial domain for image watermarking. The mask exploits the properties of human visual system with respect to background luminance, the edge and texture masking, which are expressed by certain image features. On the use of the mask, a new double domain watermarking framework is presented. The watermark is embe...

The original quantization index modulation watermarking is largely vulnerable to valumetric scaling and constant change attacks. To overcome these two drawbacks, the normalized dither modulation (NDM) is presented in this paper. The main idea of it is to construct a gain-invariant vector with zero mean for quantization. Performance analysis shows t...

The original quantization index modulation (QIM) watermarking is largely vulnerable to volumetric scaling. To solve this problem, a gain-invariant vector for quantization is constructed through dividing the host signal by a statistical feature extracted from the target content. With this idea, the improved dither modulation (IM-DM) and spread trans...

To seek the good tradeoff between robustness and unobtrusiveness, the cover data is divided into nonoverlapping blocks and an independent distortion situation is assigned to each block, which is called localized quality evaluation. Two specific implementations applying the Signal to Noise Ratio and Watson' s visual model as the quality metrics are...

This paper presents a new approach utilizing the sensor's pattern noise and linear prediction synthesis filter for steganography. The pattern noise is extracted from the images using denoising filter (for example wavelet-based filter). Then the approach introduces the linear prediction synthesis filter, whose parameters are derived from the extract...

This paper presents a new multibit watermarking method. The method uses multiple orthonormalized watermark patterns of the same size as the host signal. In particular, the elements of each watermark pattern follow independent normal distribution. Each bit of the transmitted message is hidden using the dither quantizers to modify the projection of t...

The two conflicting requirements of watermark invisibility and robustness are both required in most applications. The solution is to utilize a suitable perceptual quality metric (PQM) for watermarking correctly. This paper develops a new quality metric, the improved signal to noise ratio (iSNR). The improvement is done in the following two aspects:...

This paper presents a new approach on image-adaptive spread-transform dither modulation (STDM). The approach is performed in the discrete cosine transform (DCT) domain, and modifies the original STDM in such a way that the spread vector is weighted by a set of just noticeable differences (JND's) derived from Watson's model before it is added to the...

Gabor filters based features, with their good properties of space-frequency localization and orientation selectivity, seem to be the most effective features for face recognition currently. In this paper, we propose a kind of weighted Gabor complex features which combining Gabor magnitude and phase features in unitary space. Its weights are determin...

Digital Fingerprinting is a technique for the merchant who can embed unique buyer identity marks into digital media copy, and also makes it possible to identify "traitors" who redistribute their illegal copies. At present, the fingerprinting scheme generally have many difficulties and disadvantages for large-size uses problems involve in the code c...

In a general additive watermarking model, a watermark signal is perceptually shaped and scaled with a global gain factor before embedding. This paper presents a new image-adaptive watermarking scheme based on perceptually shaping watermark blockwise. Instead of the global gain factor, a localized one is used for each block. And Watson's DCT-based v...

It has been demonstrated that combining the decisions of several classifiers can lead to better recognition results. The combination can be implemented using a variety of schemes, among which voting method is the simplest, but it has been found to be just as effective as more complicated strategies in improving the recognition results. In this pape...

Head gestures such as nodding and shaking are often used as one of human body languages for communication with each other, and their recognition plays an important role in the advancement of human-computer interaction. As head gesture is the continuous motion on the sequential time series, the key problems of recognition are to track multi-view hea...

Head gestures such as nodding and shaking are often used as one of human body languages for communication with each other, and their recognition plays an important role in the development of Human-Computer Interaction (HCI). As head gesture is the continuous motion on the sequential time series, the key problems of recognition are to track multi-vi...

Automatic facial feature location is an important step in human-computer interaction and automatic face recognition. In spite of the considerable past research effort, precise and robust facial feature location remains a challenging problem. In this paper, we deal with the eye location problem from the perspective of information fusion and propose...

This paper presents a new approach on utilizing human visual model (HVM) for watermarking. The approach introduces the linear prediction synthesis filter, whose parameters are derived from a set of just noticeable differences estimated by HVM. After being filtered by such a filter, the watermark can be adapted to characteristics of human visual sys...

In this paper, the effect of scaling on the watermark detector is analyzed. A novel idea, watermark normalization is proposed. The original message pattern is generated with a standard and large size. When embedding, the message pattern is suited into the same size as the cover data by the sampling with equal intervals. The same operation is also a...

A feature based fragile image watermarking framework is proposed to resist vector quantization (VQ) attack. Image features are extracted to process the original watermark or generate the watermark so that the embedded watermark is not only unknown to the attacker, but also dependent on the image. Therefore, different images have different embedded...