This paper elaborates on a new class of orthonormal power-based algorithms for fast estimation and tracking of the principal or minor subspace of a vector sequence. The proposed algorithms are closely related to the natural power method that has the fastest convergence rate among many power-based methods such as the Oja method, the projection approximation subspace tracking (PAST) method, and the novel

Recently, mobile edge computing(MEC) has attracted considerable research effort, because mobile users can offload some tasks to edge servers that are closer to users than cloud servers for a better computing experience, which can bring enormous potential in next-generation wireless networks(5G). However, when users are moving, they may be far away from the edge server that undertakes the offloading

In this article, we develop the adaptive error feedback regulator design for one-dimensional heat equation with a nonlocal term and disturbances which are located all the channels. First, we construct a transformation to transform the original system into the first auxiliary system, and in this system the measurable tracking error becomes output, both the disturbances located at the in-domain and the

In the framework of asynchronous control, finite-time stabilization and finite-time bounded stabilization of linear time-varying (LTV) switched systems are investigated. A necessary and sufficient condition for finite-time stability (FTS) of LTV switched systems is proposed based on differential matrix inequalities (DMIs). Moreover, we extend the FTS result to the case of finite-time boundedness (FTB)

With Terahertz band (0.1–10 THz) technology, several nanoscale ad hoc applications could be developed, such as intrabody health monitoring, programmable material, etc. The fundamental element to ensure the functionality of these applications is the way to access the radio communication channel. The main challenge with nanocommunication is the need to efficiently share the terahertz radio spectrum to

To solve the problem of security deployment in a hybrid wireless sensor network, a novel privacy-preserving mobile coverage scheme based on trustworthiness is proposed. The novel scheme can efficiently mitigate some malicious attacks such as eavesdropping and pollution and optimize the coverage of hybrid wireless sensor networks (HWSNs) at the same time. Compared with the traditional mobile coverage

Although the Chinese economy has developed rapidly since the reform and opening up, the income distribution gap is widening year by year. The final social income distribution pattern is highly dependent on the primary distribution pattern. Therefore, the changing trend and influencing factors of labor income share have become the focus of academic research and the focus of government attention. Based

We present a new video compression framework (ViSTRA2) which exploits adaptation of spatial resolution and effective bit depth, down-sampling these parameters at the encoder based on perceptual criteria, and up-sampling at the decoder using a deep convolution neural network. ViSTRA2 has been integrated with the reference software of both the HEVC (HM 16.20) and VVC (VTM 4.0.1), and evaluated under

The Earth’s surface changes continuously due to several natural and humanmade factors. Efficient change detection (CD) is useful in monitoring and managing different situations. The recent rise in launched hyperspectral platforms provides a diversity of spectrum in addition to the spatial resolution required to meet recent civil applications requirements. Traditional multispectral CD algorithms hardly

Elastic optical networks allow for a division of the optical spectrum into frequency slots, which can be combined to create channels with bandwidth defined by demand. Their flexibility provides greater spectral efficiency when compared with traditional optical networks with fixed grids. Traffic grooming strategies allow for even more efficiency in the use of network resources, reducing the number of

Presently, Secondary Networks (SNs) are gleaned from rising capacity with reducing interference together instead of making them energy-efficient for green communication. This paper proposes an energy-efficient optimization for resources using game in Hybrid Non-orthogonal Multiple Access (HNOMA) based Cognitive Radio Networks (CRNs). For this, also proposes SUs clustering and energy-efficient Power

This paper encounters the problem of multi-cell precoding in downlink transmission of a massive multiple input multiple output (MIMO) system, where a constant envelope precoding (CEP) structure is employed with the aim of alleviating the implementation cost as well as improving the hardware efficiency. For this purpose, first, the optimization problem of the angle of arrival (AoA)-driven multi-cell

Automatic Modulation Classification (AMC) plays an important role in many civilian applications such as spectrum monitoring (SM) and cognitive radio (CR). The majority of the AMC algorithms for MIMO systems are developed for rich scattering environments, which offer a full rank channel matrix. A rank deficient channel such as a keyhole channel severely affects the AMC performance. It is reported that

The shooting and bouncing ray approach is an important method used in ray-tracing simulations to estimate the propagation of radio waves. However, in this method, unnecessary rays, which are useless for follow-up and consume a large amount of simulation resources, may emerge. This study proposes an artificial intelligence-based acceleration solution, unlike geometry-based approaches in the literature

Minimal cognitive impairment (MCI), a potential precursor to Alzheimer’s disease (AD), may be a heterogeneous entity consisting of distinct subtypes. To evaluate this hypothesis, we applied unsupervised machine-learning to a subset of the Alzheimer’s disease Neuroimaging Initiative (ADNI) data set, and detected MCI subtypes with distinct clinical correlates. Our subtype-detection system consists of

Acoustic models of the vocal tract for articulatory speech synthesis often neglect a range of acoustic effects that are known to exist in the human vocal tract. Here we extended a basic acoustic vocal tract model by three features: the piriform fossae, transvelar acoustic coupling of the oral and nasal cavities, and sound radiation from the skin of the neck. The main goal was to find out how these

Traditional consumer finance is a modern financial service method that provides consumer loans to consumers of all classes. With the gradual improvement of China’s credit reporting system, big data credit reporting has effectively made up for the lack of traditional credit reporting and has been widely used in the consumer finance industry. In this context, the in-depth analysis of the specific application

Given the growth of wireless networks and the increase of the advantages and applications of communication networks, especially mobile ad hoc networks (MANETs), this type of network has attracted the attention of users and researchers more than before. The benefit of these types of networks in various kinds of networks and environments is that MANET does not require to hardware infrastructure to communicate

Cloud computing uses virtualization technology to provide users with different types of resources in the form of services. The third party plays a crucial role in coordinating cloud market between cloud providers and users. As for providing services or trading, the extra broker fees are required for the middleman because the third party facilitates transactions. Moreover, there is no guarantee that

An array of existing active contour models is prone to suffering from the deficiencies of poor anti-noise ability, initialization sensitivity, and slow convergence. In order to handle these problems, a robust hybrid active contour method based on bias correction is proposed in this research paper The energy functional is formulated through incorporating the adaptive edge indicator function and level

Light Field (LF) image angular super-resolution aims to synthesize a high angular resolution LF image from a low angular resolution one, and is drawing increased attention because of its wide applications. In order to reconstruct a high angular resolution LF image, many learning based LF image angular super-resolution methods have been proposed. However, most existing methods are based on LF Epipolar

We extend the theorem of Liouville on integration in finite terms to include dilogarithmic integrals. The results provide a necessary and sufficient condition for an element of the base field to have an antiderivative in a field extension generated by transcendental elementary functions and dilogarithmic integrals.

The paper investigates the effect of fractional-order parameters on the memristive features such as hysteresis lobe area, the number of pinched points, and their coordinates. In addition, the series-connected fractional-order inductor and capacitor with memristive elements are discussed where the coordinates of the pinched point move away from zero points as α changes. The second-and third-order memristive

Millimeter-wave massive MIMO systems acquire a high dimensional distorted channel matrix to perform channel estimation. The captured channel matrix is sparse and rank deficient due to low scattering at millimeter-wave bands. The reduced number of RF chains enable the indirect access of signal at each antenna. This makes it difficult to estimate the channel accurately. To address this issue, researchers

LoRa, due to its advantage of long-range communication capability, is promising for Internet of Things (IoT) and space-air-ground communications. However, the conventional MAC protocol used with LoRa is classified as an Aloha-based algorithm, which leads to drastic decrease in throughput when a huge amount of end-devices try to access the network. To achieve stable and high throughput of LoRa, we propose

The use of effective clustering algorithms can extend the life of wireless sensor networks. In general, the clustering algorithm should have the ability to reduce the energy requirement. Henceforth, this paper presents the particle swarm optimization (PSO) technique for the selection of master cluster head (MCH) and surrogate cluster head (SCH) and an efficient multidirectional routing is proposed

Wireless sensor networks (WSNs) consist of a large number of sensor nodes, which are primarily employed for collecting data from an environment of interest. Energy resources of WSN nodes are generally restricted, irreplaceable and non-rechargeable. Hence, lowering the level of energy consumption in such networks to save more energy is the key issue in the literature. Clustering, selecting the best

A 2 × 2 circularly polarized array is presented whose polarization diversity can be electronically controlled. The antenna array utilizes 180° rat-race and two pair of hybrid couplers. The antenna’s CPW feed-line comprises of a reconfigurable sequentially rotated network. Reconfigurable property is achieved by employing two pairs of PIN diodes that determine the right-handed and left-handed circular

In this paper, we proposed a 40Gbps 16QAM-OFDM polarization insensitive all-optical wavelength conversion (AOWC) system based on self-pumping structure of wide optical comb. In this scheme, the carrier suppression modulation is carried out by a laser with Mach-Zehnder modulator (MZM) to generate a wide comb with only 3 dB odd sidebands flatness. By changing the frequency selection of the optical comb

In this letter, the order recursive least squares (ORLS) is applied to the azimuth-only ULA to probe the DoA estimation under the unknown number of external sources. In the ORLS-based method, the iterative measured matrix equations are feasibly constructed by combining the two spatial modified Yule-Walker (MYW) systems of linear equations and are required to remain Hankel-block-matrix structure of

Exploiting RGB and depth information can boost the performance of semantic segmentation. However, owing to the differences between RGB images and the corresponding depth maps, such multimodal information should be effectively used and combined. Most existing methods use the same fusion strategy to explore multilevel complementary information at various levels, likely ignoring different feature contributions

Recently, a number of projected successive interference cancellation (PSIC) and projected parallel interference cancellation (PPIC) structures, which make use of the non-negativity constraint in incoherent OCDMA systems to enhance their performance, have been proposed and studied in (Seleem et al. in IEEE Commun Lett 16:1721–1724, 2012). Although these structures showed improved performance, they still

In the wireless ultraviolet sensor network, interference causes data retransmission, which is not conducive to communication between sensor nodes. Aiming at the serious communication interference problem of three-dimensional k-connected wireless ultraviolet light sensor network, this paper proposes a novel low-interference wireless ultraviolet network fault-tolerant topology control algorithm. The

In the past few years, a large body of literature has been created on downlink Non-Orthogonal Multiple Access (NOMA), employing superposition coding and Successive Interference Cancellation (SIC), in multi-antenna wireless networks. Furthermore, the benefits of NOMA over Orthogonal Multiple Access (OMA) have been highlighted. In this paper, we take a critical and fresh look at the downlink Next Generation

In-band full-duplex (IBFD) is an attractive solution for increasing the throughput of Power Line Communication (PLC) systems. In IBFD, each network node is allowed to transmit and receive simultaneously in the same frequency band. This paper discusses the importance of defining figures of merit to analyze IBFD performance, which is often forgotten by the literature that addresses IBFD from a pure system

Digital imagery and video can have content at higher resolutions than can be projected by most data projectors, which has led to a variety of techniques to improve the high-resolution perception from lower-resolution displays. However, the downsampling procedures frequently used to fit an original image or video of high-resolution into a lower-resolution projector cause a frustrating loss of fine structures

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This Special Issue of the IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS (JETCAS) is dedicated to demonstrating the latest research progress in the area of hardware security in emerging technologies.

The last decade has witnessed remarkable research advances at the intersection of machine learning (ML) and hardware security. The confluence of the two technologies has created many interesting and unique opportunities, but also left some issues in their wake. ML schemes have been extensively used to enhance the security and trust of embedded systems like hardware Trojans and malware detection. On

The flourishing of Internet of Things (IoT) has rekindled on-premise computing to allow data to be analyzed closer to the source. To support edge Artificial Intelligence (AI), hardware accelerators, open-source AI model compilers and commercially available toolkits have evolved to facilitate the development and deployment of applications that use AI at its core. This paradigm shift in deep learning

Training accurate deep learning (DL) models require large amounts of training data, significant work in labeling the data, considerable computing resources, and substantial domain expertise. In short, they are expensive to develop. Hence, protecting these models, which are valuable storehouses of intellectual properties (IP), against model stealing/cloning attacks is of paramount importance. Today’s

Flooding-based Denial-of-service (DoS) attacks have been prevalent in Network-on-Chip (NoC) architectures, due to its shared nature and open access to all the on-chip modules. A Malicious Intellectual Property (MIP) within a System-on-Chip (SoC) creates such an attack by flooding the NoC with useless packets resulting in significant bandwidth reduction. Finding the location of an MIP is crucial to

We propose TPE, a hardware-based framework to perform workload execution forensics in microprocessors. Specifically, TPE leverages custom hardware instrumentation to capture the operational profile of the Translation Lookaside Buffer (TLB), as well as process these information off-line through multiple machine learning and/or deep learning approaches, in order to identify the executed processes and

Hardware security circuits based on Physically Unclonable Functions (PUF) are finding widespread use due to increasing adoption of IoT devices. However, existing strong PUFs such as Arbiter-PUF (APUF) and its compositions are susceptible to machine learning (ML) attacks due to a linear relationship between the challenge and its response. In this paper, we present a Recurrence-based PUF (Rec-PUF) which

Quantum computing is a promising paradigm to solve computationally intractable problems. Various companies such as, IBM, Rigetti and D-Wave offer quantum computers using a cloud-based platform that possess several interesting features namely, (i) quantum hardware with various number of qubits and coupling maps exist at the cloud end that offer different computing capabilities; (ii) multiple hardware

We present a side-channel-attack (SCA) resistant asynchronous-logic (async-logic) Advanced Encryption Standard (AES) accelerator with dual-hiding SCA countermeasures, i.e. the amplitude moderation (vertical dimension) and the time moderation (horizontal dimension). There are five contributions in this paper. First, we propose an async-logic design flow with relative timing to simplify the AES realization

To lower cost and increase the utilization of Cloud Field-Programmable Gate Arrays (FPGAs), researchers have recently been exploring the concept of multi-tenant FPGAs, where multiple independent users simultaneously share the same remote FPGA. Despite its benefits, multi-tenancy opens up the possibility of malicious users co-locating on the same FPGA as a victim user, and extracting sensitive information

Commercial electronic design automation (EDA) tools typically focus on optimizing the power, area, and speed of integrated circuits (ICs). They rarely consider hardware security requirements. As such, existing EDA tools often directly or indirectly introduce security vulnerabilities. These security vulnerabilities can later be exploited by attackers to leak information or compromise the hardware root-of-trust

Post-quantum cryptography (PQC) refers to the cryptosystem that can resist the attacks launched from mature quantum computers in the not far future and has recently gained intensive attention from the research community as most of the existing public-key cryptosystems are vulnerable to attacks from quantum computers. Ring-Learning-with-Errors (Ring-LWE)-based scheme is an essential type of the lattice-based

This paper demonstrates a hardware encryption algorithm that can be integrated directly with sensors on the same chip. In contrast to using power-hungry microprocessors and software implementations, the encryption algorithm was based on a Lorenz chaotic system and was implemented as time scaling chaotic shift keying (TS-CSK). The coupled differential equations of TS-CSK were implemented using low power

This paper presents a compressed sensing (CS) based encryption scheme for wireless neural recording. An ultrahigh efficiency was achieved by leveraging CS for simultaneous data compression and encryption. CS enables sub-Nyquist sampling of neural signals by taking advantage of their intrinsic sparsity, while the CS process simultaneously encrypts the data with the sampling matrix being the cryptographic

Information flow tracking (IFT) is a widely used methodology for ensuring data confidentiality and/or integrity in electronic systems and many such methods have been developed at various software or hardware description levels. Among them, Proof-Carrying Hardware Intellectual Property (PCHIP) introduced an IFT methodology for digital hardware designs described in hardware description languages (HDLs)

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1 INTRODUCTION Real-world systems have to operate in uncertain and changing environments, thus the necessity to design feedback controllers which can adapt to such uncertainties. Controllers which are designed to satisfy this goal are called adaptive controllers. We can classify adaptive control into three main subclasses, for example, Reference : Classical model-based adaptive control, which mainly