Subjects: Mathematics >> Statistics and Probability Subjects: Statistics >> Mathematical Statistics Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2024-05-22
Abstract： Statistical independence is a core concept in statistics and machine learning. Representing and measuring independence are of fundamental importance in related fields. Copula theory provides the tool for representing statistical independence, while Copula Entropy (CE) presents the tool for measuring statistical independence. This paper first introduces the theory of CE, including its definition, theorem, properties, and estimation method. The theoretical applications of CE to structure learning, association discovery, variable selection, causal discovery, system identification, time lag estimation, domain adaptation, multivariate normality test, two-sample test, and change point detection are reviewed. The relationships between the theoretical applications and their connection to correlation and causality are discussed. The frameworks based on CE, the kernel method, and distance correlation for measuring statistical independence and conditional independence are compared. The advantage of CE based on methods over the other comparable methods is evaluated with simulated and real data. The applications of CE in theoretical physics, astrophysics, geophysics, theoretical chemistry, cheminformatics, materials science, hydrology, climatology, meteorology, environmental science, ecology, animal morphology, agronomy, cognitive neuroscience, motor neuroscience, computational neuroscience, psychology, system biology, bioinformatics, clinical diagnostics, geriatrics, psychiatry, public health, economics, management, sociology, pedagogy, computational linguistics, mass media, law, political science, military science, informatics, energy, food engineering, architecture, civil engineering, transportation, manufacturing, reliability, metallurgy, chemical engineering, aeronautics and astronautics, weapon, automobile, electronics, communication, high performance computing, cybersecurity, remote sensing, ocean, and finance are briefly introduced.
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Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science Subjects: Physics >> Electromagnetism, Optics, Acoustics, Heat Transfer, Classical Mechanics, and Fluid Dynamics Subjects: Astronomy >> Astrophysical processes submitted time 2024-05-22
Abstract： The electromagnetic fields of point sources with time varying charges moving in the vacuum are derived using the Liénard-Wiechert potentials. The properties of the propagation velocities and the Doppler effect are discussed based on their far fields. The results show that the velocity of the electromagnetic waves and the velocity of the sources cannot be added like vectors; the velocity of electromagnetic waves of moving sources are anisotropic in the vacuum; the transverse Doppler shift is intrinsically included in the fields of the moving sources and is not a pure relativity effect caused by time dilation. Since the fields are rigorous solutions of the Maxwell’s equations, the findings can help us to abort the long-standing misinterpretations concerning about the classic mechanics and the classic electromagnetic theory. Although it may violate the theory of the special relativity, we show mathematically that, when the sources move faster than the light in the vacuum, the electromagnetic barriers and the electromagnetic shock waves can be clearly predicted using the exact solutions. Since they cannot be detected by observers in the region outside their shock wave zones, an intuitive and reasonable hypothesis can be made that the superluminal sources may be considered as a kind of electromagnetic blackholes.
Peer Review Status:Awaiting Review
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science Subjects: Physics >> Electromagnetism, Optics, Acoustics, Heat Transfer, Classical Mechanics, and Fluid Dynamics Subjects: Electronics and Communication Technology >> Optoelectronics and Laser Subjects: Physics >> Geophysics, Astronomy, and Astrophysics Subjects: Physics >> The Physics of Elementary Particles and Fields submitted time 2024-04-08
Abstract： The Einstein’s theory of special relativity is based on his two postulates. The first is that the laws of physics are the same in all inertial reference frames. The second is that the velocity of light in the vacuum is the same in all inertial frames. The theory of special relativity is considered to be supported by a large number of experiments. This paper revisits the two postulates according to the new interpretations to the exact solutions of moving sources in the laboratory frame. The exact solutions are obtained using the classic Maxwell’s theory, which clearly show that the propagation velocity of the electromagnetic waves of moving sources in the vacuum is not isotropic; the propagation velocity of the electromagnetic waves and the moving velocity of the sources cannot be added like vectors; the transverse Doppler effect is intrinsically included in the fields of the moving sources. The electromagnetic sources are subject to the Newtonian mechanics, while the electromagnetic fields are subject to the Maxwell’s theory. We argue that since their behaviors are quite different, it is not a best choice to try to bind them together and force them to undergo the same coordinate transformations as a whole, like that in the Lorentz transformations. Furthermore, the Maxwell’s theory does not impose any limitations on the velocity of the electromagnetic waves. To assume that all objects cannot move faster than the light in the vacuum need more examinations. We have carefully checked the main experiment results that were considered as supporting the special relativity. Unfortunately, we found that the experimental results may have been misinterpreted. We here propose a Galilean-Newtonian-Maxwellian relativity, which can give the same or even better explanations to those experimental results.
Peer Review Status:Awaiting Review
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science Subjects: Computer Science >> Other Disciplines of Computer Science Subjects: Engineering and technical science >> Engineering Mathematics submitted time 2024-03-30
Abstract： What is intelligence? is one of the core key questions of artificial intelligence, but there is no universally accepted definition. Based on the relationship between intelligence and life, this paper proposes that intelligence is the basic ability and characteristic attribute of living organisms, and it is the ability to achieve the maximum amount of information with the minimum energy as much as possible, and adapt to the environment and maintain existence through information processing. On this basis, this paper puts forward a new view that intelligence is the ability to convert material energy and information, further puts forward new concepts such as the measurement calculation method of intelligence, average intelligence, and comprehensive intelligence, and finally discusses the quantitative conversion relationship between matter, energy and information, points out the upper bound of intelligence and the lower bound of energy conversion into information, and further gives a dimensionless calculation formula for intelligence measurement in order to facilitate practical application. A feasible calculation method is given for the quantitative analysis of the intelligence of the intelligent system..
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Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2024-01-06
Abstract： In recent years， the industrial process has been developing towards complexity and large-scale， which has posed a series of challenges for traditional fault diagnosis techniques to solve practical industrial process problems. With the superior performance and unique potential of deep learning in feature extraction and pattern recognition， the application of deep learning technology to fault diagnosis has become a current research focus. Therefore， this article introduces several typical fault diagnosis methods based on deep learning. Finally， the obstacles in the application of deep learning to fault diagnosis are discussed， and the future research directions are prospected.
Peer Review Status:Awaiting Review
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2024-01-06
Abstract： Although the current 3D face reconstruction methods based on a single image can recover fine geometric details, these methods have limitations. The faces generated by some methods can't be really animated because they don't model how wrinkles change with expressions. Other methods are trained on high-quality facial scanning, and cannot be well extended to images of natural scenes. The method used in the report can return to the details of three-dimensional face shapes and animations, which are specific to individuals but can change with expressions. The model of this method can be trained to generate a UV displacement map from a low-dimensional potential representation composed of person-specific detail parameters and general expression parameters, while the regression quantity can be trained to predict details, shapes, expressions, postures and lighting parameters from a single image. In order to achieve this, this method introduces a new loss of detail consistency, which separates people-specific details from wrinkles that depend on expressions. This unwrapping makes it possible to synthesize realistic personal specific wrinkles by controlling expression parameters while keeping personal specific details unchanged. This method is learned from images of natural scenes, and there is no paired 3D data supervision.
Peer Review Status:Awaiting Review
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science Subjects: Biology >> Biological Evolution Subjects: Biology >> Biomathematics Subjects: Physics >> Interdisciplinary Physics and Related Areas of Science and Technology Subjects: Biology >> Genetics submitted time 2023-10-15
Zhang, Zecheng
Liu, Chunxiuzi
Zhu, Yingjun
Peng, Lu
Qiu, Weiyi
Tang, Qianyuan
Liu, He
Zhang, Ke
Di, Zengru
Liu, Yu
Abstract： Background: In bioinformatics, tools like multiple sequence alignment and entropy methods probe sequence information and evolutionary relationships between species. Although powerful, they might miss crucial hierarchical relationships formed by the reuse of repetitive subsequences like duplicons and transposable elements. Such relationships are governed by “evolutionary tinkering'', as described by Fran c{c}ois Jacob. The newly developed Ladderpath theory provides a quantitative framework to describe these hierarchical relationships.
Results: Based on this theory, we introduce two indicators: order-rate $ eta$, characterizing sequence pattern repetitions and regularities, and ladderpath-complexity $ kappa$, characterizing hierarchical richness within sequences, considering sequence length. Statistical analyses on real amino acid sequences showed: (1) Among the typical species analyzed, humans possess relatively more sequences with large $ kappa$ values. (2) Proteins with a significant proportion of intrinsically disordered regions exhibit increased $ eta$ values. (3) There are almost no super long sequences with low $ eta$. We hypothesize that this arises from varied duplication and mutation frequencies across different evolutionary stages, which in turn suggests a zigzag pattern for the evolution of protein complexity. This is supported by our simulations and examples from protein families such as Ubiquitin and NBPF.
Conclusions: Our method emphasizes “how objects are generated'', capturing the essence of evolutionary tinkering and reuse. The findings hint at a connection between sequence orderliness and structural uncertainty, and suggest that different species or those in varied environments might adopt distinct protein elongation strategies. These insights highlight our method's value for further in-depth evolutionary biology applications.
Peer Review Status:Awaiting Review
Subjects: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc. Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-10-12
Abstract： Stereo vision is based on the principle of human binocular and insect compound eye depth vision, obtaining multiple digital images of the surrounding scene from different angles through multiple cameras, obtaining corresponding points on multiple images through stereo matching technology, and reconstructing 3D object images from the parallax information of corresponding points. The neurobiological mechanism of the existing Iterative reconstruction and stereo matching methods of binocular vision is still unknown, The neurobiological mechanism of dual view stereo vision is studied, and the Iterative reconstruction formula of dual view and multi view stereo vision is given. The conclusions obtained are consistent with the theory of visual neuroscience
Peer Review Status:Awaiting Review
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-02-14 Cooperative journals: 《桂林电子科技大学学报》
Abstract： Aiming at the influence of the noise and other factors in the process of classical correlation power analysis, based
on the linear correlation between Hamming weight and power traces, a correlation power analysis method for AES cryptographic
chip is proposed. According to the uneven distribution of the median Hamming weight of the S-box output of the
cryptographic algorithm, a set of plaintexts with strong correlation with the power traces is obtained by filtering the correct
keys and the wrong keys by using the discrimination ratio. In the stage of key recovery, the leakage points of the first two
S-boxes are found by observing this set of plaintext inputs, and the leakage intervals of the remaining 14 S-boxes are found
one by one by using the separate guessing method, so that the key information of the remaining bytes can be captured without
traversing all power traces. The experimental analysis of AT89S52 chip shows that the proposed method can correctly
recover the one-byte key of AES with 90% success rate by using only 9 plaintexts and corresponding power traces, and the
computational complexity is only 4.1% of the classical correlation power analysis, which significantly improves the efficiency
of the correlation power analysis.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-02-14 Cooperative journals: 《桂林电子科技大学学报》
Abstract： Aiming at the structure of the lightweight authentication encryption algorithm ASCON, a differential power analysis)
method is proposed. It combines the implementation characteristics of the algorithm S-box, uses the Hamming weight
model as the power consumption discrimination function, groups the traces, and recovers the master key for encryption.
Furthermore, for the "ghost peaks" what appear in DPA attacks, a traces preprocessing method is given. First, the traces
are grouped according to plaintext and averaged, and then DPA attacks are launched on the preprocessed traces. The 44 bit
master key of ASCON cipher can be recovered by attacking its sa permutation, where 1 500 traces are collected. In addition,
the time required to directly attack the original traces is 21 849.888 9 ms, and the time required to attack the preprocessed
traces is 198.911 3 ms. After preprocessing the traces, the time taken to attack the preprocessed traces is about 1/109 of
that of directly attacking the original traces.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-02-14 Cooperative journals: 《桂林电子科技大学学报》
Abstract： Aiming at the problem that the sorting clustering positioning algorithm has low matching accuracy, and there are
abnormal fingerprint points in the fingerprint points used for position calculation, a Wi-Fi positioning algorithm with matching
optimization and distance assistance is proposed. According to the user's front and back position, distance and step
length, a matching deviation detection model is designed to determine the user's abnormal position and matching deviation;
the adjacent elements in the sorted received signal strength vector are compared with the set threshold to determine the
change position of the sorting feature vector of the point to be located, achieve the purpose of correction by exchange, and
obtain the corrected and merged class matching result; according to the distance between the user's position determined in the
time period m before the positioning and the fingerprint point in the matching class, the abnormal fingerprint points used for
position calculation are eliminated, so as to achieve more accurate indoor positioning. The simulation results show that the
class matching accuracy and the average positioning accuracy of the proposed algorithm are improved respectively by 17%
and 22%.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-02-14 Cooperative journals: 《桂林电子科技大学学报》
Abstract： Aiming at the problem of blurred target position and high sidelobe when the back projection algorithm (BP algorithm)
is imaging multi-targets, after analyzing the accumulation characteristics of the FDA target echo amplitude, a target
imaging method of frequency diversity array radar based on clustering and coherent superposition is proposed. In the analysis
and Simulation of BP algorithm imaging process, it is found that the target point has the characteristics of energy concentration
and energy difference with the virtual image point. The K-means clustering algorithm can make full use of these characteristics
of the target point to extract and classify the target points in the radar imaging area, and only compensate the time
delay of the grid points of the specific cluster after classification, and then stack the echo amplitude, Thus, the energy value
of the time delay compensation grid points in the imaging region is obtained, and finally the multi-target clear two-dimensional
imaging is realized. The simulation results show that the proposed method can effectively solve the problems of fuzzy
position and high sidelobe when BP algorithm imaging multi-target, and improve the accuracy of imaging results.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-02-14 Cooperative journals: 《桂林电子科技大学学报》
Abstract： UAV swarms are widely used in radar signal interception due to their advantages of wide sensing range and rapid
information sharing. Aiming at the problem that the signal samples intercepted by UAV cluster are difficult to be fused and
analyzed directly, and the recognition accuracy of multi-function radar (MFR) working mode is low under the condition of
few training samples and unbalanced working mode samples, an MFR working mode recognition method based on smooth
graph signal generated by self-organizing map (SOM) clustering is proposed. Firstly, the intercepted signal samples are
clustered by using distributed SOM algorithm to extract the similarity between samples; Then, according to the clustering
results, the signal sample set is characterized by smooth graph signal, and the correlation of signal samples under the same
working mode is established; Finally, the graph attention network is used to fuse and classify the graph node data of the above
graph signals to complete the MFR working pattern recognition. The experimental results show that, when the imbalance
of working mode samples is about 10∶1 and the number of training samples in each class is 25, the recognition accuracy
and F1 measure of this method are improved by 22.8% and 22.34% respectively compared with the existing methods, and
can be applied to the case of noise interference.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-02-14 Cooperative journals: 《桂林电子科技大学学报》
Abstract： Aiming at the problem of medium parameter estimation around buried objects, a method of medium parameter estimation
based on image entropy is proposed. Firstly, the point spread function (PSF) of frequency diversity array ground
penetrating radar (FDA-GPR) in medium is derived, and the relationship between PSF and back projection imaging algorithm
is analyzed. Then, the imaging results of FDA-GPR and UWB-GPR are compared and analyzed. For the same region
containing the target to be imaged, the medium parameters have a great influence on the propagation velocity of electromagnetic
wave. When different medium parameters are used to image the region, the imaging results are also different. The image
entropy of the imaging results under different parameters is calculated. The smaller the image entropy of the imaging
results is, the better the focusing degree of the imaging is, and the closer the corresponding medium parameters are to their
true values. The experimental results show that:when the conductivity of the medium is not zero, FDA-GPR has better performance
in target location and imaging than UWB-GPR, and when the target is a slender target, the proposed parameter
estimation method can effectively estimate the parameters of the medium around the target
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-02-14 Cooperative journals: 《桂林电子科技大学学报》
Abstract： Aiming at the problem of the large number of array elements and low utilization rate of the three-dimensional synthetic
aperture radar (3D-FDA-SAR) imaging method of frequency diversity arrays, a 3D-FDA-SAR imaging method based
on multiple input and multiple output arrays is proposed. The frequency diversity array of 3D-FDA-SAR tangent track direction
is changed to multiple input multiple output frequency diversity array. The multiple input multiple output frequency
diversity array moves with the moving platform to form a synthetic aperture along the track direction, combined with the
tangent track direction The real array is combined with a virtual two-dimensional frequency diversity array plane to obtain the
downward-looking three-dimensional imaging capability of the target. Firstly, a multi-input multi-output 3D-FDA-SAR imaging
model and signal model are established, using multi-input multi-output technology, the waveform quadrature signal
single-frequency narrowband signal is sent at the transmitting end, and all the transmitting arrays are received through the
full-frequency receiving mode at the receiving end. The echo signal reflected by the target is separated by a quadrature
matched filter to obtain the echo data of different receiving and sending channels, and then the echo data is imaged by the
backward projection algorithm, and finally the three-dimensional imaging result of the target is obtained. Experimental simulation
results show that the 3D-FDA-SAR imaging method based on multiple-input multiple-output arrays uses a small
number of array elements, improves the utilization of the array elements, and obtains the three-dimensional imaging capability
of downward-looking targets.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-02-14 Cooperative journals: 《桂林电子科技大学学报》
Abstract： The hardware design of phased array three-dimension synthetic aperture radar (SAR) system based on wideband
transmission signals is complicated, and the received signals are difficult to separate. By applying the frequency diverse array
(FDA) to 3D-SAR, each array element only needs to transmit a single frequency signal to obtain wideband observation performance,
which greatly reduces the hardware requirements of system. However, due to the space-frequency sparseness of
FDA echo signals, the resolution is limited and the sidelobes of radar images are relatively high when using the back projection
(BP) algorithm based on matched filtering. To solve this problem, this paper proposes a random frequency diverse array
3D-SAR imaging method based on compressed sensing (CS). The array elements in the tangent-track and the observation
positions in the along-track are selected randomly and sparsely to realize two-dimensional sparse sampling of echo data.
In the imaging part, orthogonal matching pursuit (OMP) algorithm is used to reconstruct the scattering coefficient of targets.
Simulation and experimental results show that CS method not only reduces the data processing amount of FDA-3DSAR
system during imaging, but also effectively suppresses the sidelobes of radar images, and the imaging quality is significantly
improved. By using the compressed sensing algorithm, FDA-3D-SAR can accurately reconstruct the information of
space targets when the echo is sparse, which verifies the rationality and effectiveness of the proposed method.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2023-02-14 Cooperative journals: 《桂林电子科技大学学报》
Abstract： The reconstruction problem of spatio-temporal signals can be cast as recovering differential smooth time-varying
graph signals. For the optimization problem, the existing distributed algorithm based on gradient descent method shows
slow convergence when the condition number of the Hessian matrix of the problem is large which leads to a large reconstruction
error when the maximum iteration number is limited in an observation interval. Therefore, an online distributed reconstruction
algorithm based on approximate Newton's method is proposed in the paper, whose principle is to decompose the
original optimization problem into a series of local problems on subgraphs through subgraph decomposition and find these
solutions, and then obtain the approximate global optimal solution via fusion average of local solutions between each subgraph.
According to the gap between the approximate solution and the actual one, it can be proved that the decompostion
and fusion matrix obtained in this way is sparse and can be regarded as the approximate Hessian inverse. Hence, the algorithm
replaces the approximate matrix into the classical Newton iterative formula which can be implemented in a distributed
manner due to the structural sparsity of the approximate matrix. Simulation results show that the proposed algorithm has
faster convergence rate and smaller reconstruction error, and requires less communication cost compared with the existing
algorithm.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2022-10-26 Cooperative journals: 《桂林电子科技大学学报》
Abstract： To solve the problem that agents cannot make effective decisions under local observation, a conflict resolution
method combined with deep reinforcement learning is proposed. Based on DDQN algorithm, this method uses the characteristics
of reinforcement learning mode to calculate the cumulative return of agent and determine the priority of agent through
the return value, so as to achieve the purpose of conflict resolution. The method is evaluated by simulating the traffic jam in
real life, and the experimental results show that the method can effectively solve the agent conflict.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science Subjects: Physics >> Interdisciplinary Physics and Related Areas of Science and Technology submitted time 2022-08-15
Abstract： The notion of information and complexity are important concepts in many scientific fields such as molecular biology, evolutionary theory and exobiology. Many measures of these quantities are either difficult to compute, rely on the statistical notion of information, or can only be applied to strings. Based on assembly theory, we propose the notion of a ladderpath, which describes how an object can be decomposed into hierarchical structures using repetitive elements. From the ladderpath two measures naturally emerge: the ladderpath-index and the order-index, which represent two axes of complexity. We show how the ladderpath approach can be applied to both strings and spatial patterns and argue that all systems that undergo evolution can be described as ladderpaths. Further, we discuss possible applications to human language and the origin of life. The ladderpath approach provides an alternative characterization of the information that is contained in a single object (or a system) and could aid in our understanding of evolving systems and the origin of life in particular.
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2022-07-09
Abstract：
[Objective]This paper studies the relationship between information volume and mass, energy, and time, through analyses of definition and properties of information volume based on the information sextuple model, in order to provide a theoretical reference for research and applications of information science, especially quantum information.
[Methods] Based on the information sextuple model in the Objective Information Theory, along with the theories of quantum information, we studied the information volume effect under a variety of combinatorial conditions, and strictly derived the relationship between information and matter, energy and, time through mathematical axiomatic methods.
[Results] We proved that the information capacity based on the information entropy is a special case of the definition of information volume in the Objective Information Theory. Furthermore, we estimated the information volumne of a single quantum carrier, derived the relationship formula between information volume and mass, energy and, time. Based on this, we estimated and comparatively analyzed the information volume existed in the universe.
[Limitations] These theoretical results are in need of validation with empirical physical studies and applications of complex information systems science
[Conclusions] The connotation of information volume of the Objective Information Theory can profoundly and accurately, to a certain extent, reveal the relationship among the three basic elements of the objective world—that is, matter, energy and information, demonstrating a good universal significance and application prospect.
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Peer Review Status:Awaiting Review
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