arXiv subjects

Yong Fang

Publications and source records attributed to Yong Fang.

33 records · Page 2Linked to original sources

arXiv2021

Designation of Intra-layer and Intercalated High Entropy Quasi-2D Compounds

Here, we designed two promising schemes to realize the high-entropy structure in a series of quasi-two-dimensional compounds, transition metal dichalcogenides (TMDCs). In the intra-layer high-entropy plan, (HEM)X2 compounds with high-entropy structure in the MX2 slabs were obtained, here HEM means high-entropy metals, such as TiZrNbMoTa. And superconductivity with a Tc~7.4 K was found in a Mo-rich HEMX2. On the other hand, in the intercalation plan, we intercalated HEM-atoms (FeCoCrNiMn) into the gap between the sandwiched-MX2 slabs resulting in a series of (HEM)xMX2 compounds, x in the range of 0~0.5, in which HEM is mainly composed of 3d transition metal elements, such as FeCoCrNiMn. As the introduction of multi-component magnetic atoms, ferromagnetic spin-glass states with strong 2D characteristics ensued. Tuning the x content, three kinds of two in the high-entropy intercalated layer were observed including the 1*1 triangular lattice and two kinds of superlattices \sqrt3*\sqrt3 and \sqrt3*2 in x=0.333 and x>0.5, respectively. Meanwhile, the spin frustration in the two-dimensional high-entropy magnetic plane will be enhanced with the development of \sqrt3*\sqrt3 and will be reduced significantly when changing into the \sqrt3*2 phase. The high-entropy TMDCs and versatile two-dimensional high-entropy structures found by us possess great potentials to find new physics in low-dimensional high-entropy structures and future applications.

cond-mat.mtrl-sci↗

arXiv2021

Distributed Arithmetic Coding for Sources with Hidden Markov Correlation

Distributed arithmetic coding (DAC) has been shown to be effective for Slepian-Wolf coding, especially for short data blocks. In this letter, we propose to use the DAC to compress momery-correlated sources. More specifically, the correlation between sources is modeled as a hidden Markov process. Experimental results show that the performance is close to the theoretical Slepian-Wolf limit.

cs.IT↗

arXiv2019

Decoding Polar Codes via Weighted-Window Soft Cancellation for Slowly-Varying Channel

Polar codes are a class of {\bf structured} channel codes proposed by Arıkan based on the principle of {\bf channel polarization}, and can {\bf achieve} the symmetric capacity of any Binary-input Discrete Memoryless Channel (B-DMC). The Soft CANcellation (SCAN) is a {\bf low-complexity} {\bf iterative} decoding algorithm of polar codes outperforming the widely-used Successive Cancellation (SC). Currently, in most cases, it is assumed that channel state is perfectly {\bf known} at the decoder and remains {\bf constant} during each codeword, which, however, is usually unrealistic. To decode polar codes for {\bf slowly-varying} channel with {\bf unknown} state, on the basis of SCAN, we propose the Weighted-Window SCAN (W$^2$SCAN). Initially, the decoder is seeded with a coarse estimate of channel state. Then after {\bf each} SCAN iteration, the decoder progressively refines the estimate of channel state with the {\bf quadratic programming}. The experimental results prove the significant superiority of W$^2$SCAN to SCAN and SC. In addition, a simple method is proposed to verify the correctness of SCAN decoding which requires neither Cyclic Redundancy Check (CRC) checksum nor Hash digest.

cs.IT↗

arXiv2019

Capturing the symptoms of malicious code in electronic documents by file's entropy signal combined with Machine learning

Abstract-Email cyber-attacks based on malicious documents have become the popular techniques in today's sophisticated attacks. In the past, persistent efforts have been made to detect such attacks. But there are still some common defects in the existing methods including unable to capture unknown attacks, high overhead of resource and time, and just can be used to detect specific formats of documents. In this study, a new Framework named ESRMD (Entropy signal Reflects the Malicious document) is proposed, which can detect malicious document based on the entropy distribution of the file. In essence, ESRMD is a machine learning classifier. What makes it distinctive is that it extracts global and structural entropy features from the entropy of the malicious documents rather than the structural data or metadata of the file, enduing it the ability to deal with various document formats and against the parser-confusion and obfuscated attacks. In order to assess the validity of the model, we conducted extensive experiments on a collected dataset with 10381 samples in it, which contains malware (51.47%) and benign (48.53%) samples. The results show that our model can achieve a good performance on the true positive rate, precision and ROC with the value of 96.00%, 96.69% and 99.2% respectively. We also compared ESRMD with some leading antivirus engines and prevalent tools. The results showed that our framework can achieve a better performance compared with these engines and tools.

cs.CY↗

arXiv2017

Low-Latency Multiuser Two-Way Wireless Relaying for Spectral and Energy Efficiencies

The paper considers two possible approaches, which enable multiple pairs of users to exchange information via multiple multi-antenna relays within one time-slot to save the communication bandwidth in low-latency communications. The first approach is to deploy full-duplexes for both users and relays to make their simultaneous signal transmission and reception possible. In the second approach the users use a fraction of a time slot to send their information to the relays and the relays use the remaining complementary fraction of the time slot to send the beamformed signals to the users. The inherent loop self-interference in the duplexes and inter-full-duplexing-user interference in the first approach are absent in the second approach. Under both these approaches, the joint users' power allocation and relays' beamformers to either optimize the users' exchange of information or maximize the energy-efficiency subject to user quality-of-service (QoS) in terms of the exchanging information throughput thresholds lead to complex nonconvex optimization problems. Path-following algorithms are developed for their computational solutions. The provided numerical examples show the advantages of the second approach over the first approach.

cs.IT↗

arXiv2013

Power minimization for OFDM Transmission with Subcarrier-pair based Opportunistic DF Relaying

This paper develops a sum-power minimized resource allocation (RA) algorithm subject to a sum-rate constraint for cooperative orthogonal frequency division modulation (OFDM) transmission with subcarrier-pair based opportunistic decode-and-forward (DF) relaying. The improved DF protocol first proposed in [1] is used with optimized subcarrier pairing. Instrumental to the RA algorithm design is appropriate definition of variables to represent source/relay power allocation, subcarrier pairing and transmission-mode selection elegantly, so that after continuous relaxation, the dual method and the Hungarian algorithm can be used to find an (at least approximately) optimum RA with polynomial complexity. Moreover, the bisection method is used to speed up the search of the optimum Lagrange multiplier for the dual method. Numerical results are shown to illustrate the power-reduction benefit of the improved DF protocol with optimized subcarrier pairing.

cs.IT↗

arXiv2013

Novel Subcarrier-pair based Opportunistic DF Protocol for Cooperative Downlink OFDMA

A novel subcarrier-pair based opportunistic DF protocol is proposed for cooperative downlink OFDMA transmission aided by a decode-and-forward (DF) relay. Specifically, user message bits are transmitted in two consecutive equal-duration time slots. A subcarrier in the first slot can be paired with a subcarrier in the second slot for the DF relay-aided transmission to a user. In particular, the source and the relay can transmit simultaneously to implement beamforming at the subcarrier in the second slot for the relay-aided transmission. Each unpaired subcarrier in either the first or second slot is used by the source for direct transmission to a user without the relay's assistance. The sum rate maximized resource allocation (RA) problem is addressed for this protocol under a total power constraint. It is shown that the novel protocol leads to a maximum sum rate greater than or equal to that for a benchmark one, which does not allow the source to implement beamforming at the subcarrier in the second slot for the relay-aided transmission. Then, a polynomial-complexity RA algorithm is developed to find an (at least approximately) optimum resource allocation (i.e., source/relay power, subcarrier pairing and assignment to users) for either the proposed or benchmark protocol. Numerical experiments illustrate that the novel protocol can lead to a much greater sum rate than the benchmark one.

cs.IT↗

arXiv2011

2D Sparse Signal Recovery via 2D Orthogonal Matching Pursuit

Recovery algorithms play a key role in compressive sampling (CS). Most of current CS recovery algorithms are originally designed for one-dimensional (1D) signal, while many practical signals are two-dimensional (2D). By utilizing 2D separable sampling, 2D signal recovery problem can be converted into 1D signal recovery problem so that ordinary 1D recovery algorithms, e.g. orthogonal matching pursuit (OMP), can be applied directly. However, even with 2D separable sampling, the memory usage and complexity at the decoder is still high. This paper develops a novel recovery algorithm called 2D-OMP, which is an extension of 1D-OMP. In the 2D-OMP, each atom in the dictionary is a matrix. At each iteration, the decoder projects the sample matrix onto 2D atoms to select the best matched atom, and then renews the weights for all the already selected atoms via the least squares. We show that 2D-OMP is in fact equivalent to 1D-OMP, but it reduces recovery complexity and memory usage significantly. What's more important, by utilizing the same methodology used in this paper, one can even obtain higher dimensional OMP (say 3D-OMP, etc.) with ease.

cs.IT↗

arXiv2010

Application of DAC Codeword Spectrum: Expansion Factor

Distributed Arithmetic Coding (DAC) proves to be an effective implementation of Slepian-Wolf Coding (SWC), especially for short data blocks. To study the property of DAC codewords, the author has proposed the concept of DAC codeword spectrum. For equiprobable binary sources, the problem was formatted as solving a system of functional equations. Then, to calculate DAC codeword spectrum in general cases, three approximation methods have been proposed. In this paper, the author makes use of DAC codeword spectrum as a tool to answer an important question: how many (including proper and wrong) paths will be created during the DAC decoding, if no path is pruned? The author introduces the concept of another kind of DAC codeword spectrum, i.e. time spectrum, while the originally-proposed DAC codeword spectrum is called path spectrum from now on. To measure how fast the number of decoding paths increases, the author introduces the concept of expansion factor which is defined as the ratio of path numbers between two consecutive decoding stages. The author reveals the relation between expansion factor and path/time spectrum, and proves that the number of decoding paths of any DAC codeword increases exponentially as the decoding proceeds. Specifically, when symbols `0' and `1' are mapped onto intervals [0, q) and [(1-q), 1), where 0.5<q<1, the author proves that expansion factor converges to 2q as the decoding proceeds.

cs.IT↗

arXiv2010

Morphological dilation image coding with context weights prediction

This paper proposes an adaptive morphological dilation image coding with context weights prediction. The new dilation method is not to use fixed models, but to decide whether a coefficient needs to be dilated or not according to the coefficient's predicted significance degree. It includes two key dilation technologies: 1) controlling dilation process with context weights to reduce the output of insignificant coefficients, and 2) using variable-length group test coding with context weights to adjust the coding order and cost as few bits as possible to present the events with large probability. Moreover, we also propose a novel context weight strategy to predict coefficient's significance degree more accurately, which serves for two dilation technologies. Experimental results show that our proposed method outperforms the state of the art image coding algorithms available today.

cs.IT↗

arXiv2010

Approximation of DAC Codeword Distribution for Equiprobable Binary Sources along Proper Decoding Paths

Distributed Arithmetic Coding (DAC) is an effective implementation of Slepian-Wolf coding, especially for short data blocks. To research its properties, the concept of DAC codeword distribution along proper and wrong decoding paths has been introduced. For DAC codeword distribution of equiprobable binary sources along proper decoding paths, the problem was formatted as solving a system of functional equations. However, up to now, only one closed form was obtained at rate 0.5, while in general cases, to find the closed form of DAC codeword distribution still remains a very difficult task. This paper proposes three kinds of approximation methods for DAC codeword distribution of equiprobable binary sources along proper decoding paths: numeric approximation, polynomial approximation, and Gaussian approximation. Firstly, as a general approach, a numeric method is iterated to find the approximation to DAC codeword distribution. Secondly, at rates lower than 0.5, DAC codeword distribution can be well approximated by a polynomial. Thirdly, at very low rates, a Gaussian function centered at 0.5 is proved to be a good and simple approximation to DAC codeword distribution. A simple way to estimate the variance of Gaussian function is also proposed. Plenty of simulation results are given to verify theoretical analyses.

cs.IT↗

arXiv2005

Smooth rigidity of uniformly quasiconformal Anosov flows

We classify quasiconformal Anosov flows whose strong stable and unstable distributions are at least two dimensional and the sum of these two distributions is smooth. We deduce from this classification result the complete classification of volume-preserving quasiconformal diffeomorphisms whose stable and unstable distributions are at least two dimensional. Our central idea is to take a good time change so that perodic orbits are equi-distributed with respect to a lebesgue measure.

math.DS↗

arXiv2005

Geometric Anosov flows of dimension five with smooth distributions

We classify five dimensional Anosov flows with smooth decomposition which are in addition transversely symplectic. Up to finite covers and a special time change, we find exectly the suspensions of symplectic hyperbolic automorphisms of four dimensional toris, and the geodesic flows of three dimensional hyperbolic manifolds.

math.DS↗

arXiv2005

Pressure rigidity of three dimensional contact Anosov flows

We study the cohomological pressure introduced by R.Sharp (defined by using topological pressures of certain potentials of Anosov flows). In particular, we get the rigidity in the case that this pressure coincides with the metrical entropy, generalising related rigidity results of A.Katok and P. Foulon.

math.DS↗

arXiv2005

On orbit equivalence of quasiconformal Anosov flows

In this article, we give a quasi-final classification of quasiconformal Anosov flows. We deduce a very interesting differentable rigidity result for the orbit foliations of hyperbolic manifold of dimension at least three.

math.DS↗