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Bifurcation analysis of a diffusive radio-dependent model with spatial memory

International Journal of Biomathematics 2024年第8期17卷 309-347页

作者： Qi An Xingyu Guo Xuebing Zhang College of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing 210044 P.R.China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing 210044 P.R.China

This is an Open Access article published by World Scientific Publishing *** is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0(CC BY-NC-ND)License,which permits use,distribution and reproduction,provided that the original work is properly cited,the use is non-commercial and no modifications or adaptations are *** cognitive abilities of animals,such as memory,have a significant impact on their movement in *** this paper,we consider a radio-dependent model with memorybased diffusion under the conditions of Neumann *** stability of a positive equilibrium and the existence of the Turing-Hopf bifurcation induced by memory diffusion and memory delay are carried out in ***,our findings indicate that with a relatively short average memory period,the large memory diffusion can stabilize an otherwise unstable *** addition,the third-order truncated normal form for the Turing-Hopf bifurcation restricted to the central manifold is derived,which can reveal the generation of some steady-state and time-periodic solutions with spatial *** coefficients within the normal form are systematically determined through matrix operations,and these results can also be applied to other models with memory ***,leveraging the theoretical findings,we elucidated the intricate spatial-temporal dynamics and their associated parameter scopes caused by Turing-Hopf bifurcation through numerical simulations.

关键词： Spatial memory normal form Turing-Hopf bifurcation spatio-temporal patterns periodic solutions

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The Optimal Closed-Form Linear Canonical Wigner Distribution 6

The Optimal Closed-Form Linear Canonical Wigner Distribution

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6th International Conference on information Communication and Signal Processing, ICICSP 2023

作者： Zhang, Zhichao School of Mathematics and Statistics Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing China

ISBN: (纸本)9798350339994

This study devotes to Heisenberg's uncertainty inequalities under the closed-form instantaneous cross-correlation function Wigner distribution (CICFWD), whose generalizability enables it to be a representative Wigner distribution (WD) in the linear canonical transform (LCT) domain. A relation between the spread in the time-CICFWD domain and the spreads and moments in LCT domains is established. We then obtain two versions of lower bounds on the uncertainty product of spreads in time-CICFWD and LCT-CICFWD domains. The first is the tightest universal lower bound for all signals, and the other is a lower bound for complex-valued signals. As a result, uncertainty principles for the traditional WD are revisited. The optimal LCT free parameters selection problems of the CICFWD are also well-addressed from the perspectives of the highest time-frequency resolution and its best estimation accuracy, respectively. © 2023 IEEE.

关键词： linear canonical Wigner distribution lower bound time-frequency resolution uncertainty principle

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Optimizing Parallelization Strategies for the Big-Means Clustering Algorithm 14th

Optimizing Parallelization Strategies for the Big-Means Cl...

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14th International Conference on Optimization and Applications, OPTIMA 2023

作者： Mussabayev, Ravil Mussabayev, Rustam Department of Mathematics University of Washington Padelford Hall C-138 SeattleWA98195-4350 United States Huawei Russian Research Institute Smolenskaya Square 5 Moscow121099 Russia Institute of Information and Computational Technologies Laboratory for Analysis and Modeling of Information Processes Pushkin str. 125 Almaty050010 Kazakhstan

ISBN: (纸本)9783031487507

This study focuses on the optimization of the Big-means algorithm for clustering large-scale datasets, exploring three distinct parallelization strategies. We conducted extensive experiments to assess the computational efficiency, scalability, and clustering performance of each approach, revealing their benefits and limitations. The paper also delves into the trade-offs between computational efficiency and clustering quality, examining the impacts of various factors. Our insights provide practical guidance on selecting the best parallelization strategy based on available resources and dataset characteristics, contributing to a deeper understanding of parallelization techniques for the Big-means algorithm. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data Clustering Decomposition Divide and conquer algorithm Global optimization K-means K-means++ Minimum sum-of-squares Unsupervised learning

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Enhanced Directionality of Emission of the On-Threshold Modes of a High Refractive Index Microdisk Laser Due to a Small Piercing Hole 3

Enhanced Directionality of Emission of the On-Threshold Mode...

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3rd IEEE Ukraine Conference on Electrical and Computer Engineering, UKRCON 2021

作者： Repina, Anna I. Ketov, Ilya V. Oktyabrskaya, Alina O. Spiridonov, Alexander O. Karchevskii, Evgenii M. Kazan Federal University Department of System Analysis and Information Technologies Kazan Russia Kazan Federal University Department of Applied Mathematics Kazan Russia Kazan Federal University Laboratory of Computational Technologies and Computer Modeling Kazan Russia

ISBN: (纸本)9781665400947

We study, using the integral-equation-based in-house guaranteed-convergence numerical code, the effect of a circular air hole on the frequency, threshold gain and directionality of emission of the whispering-gallery modes of a two-dimensional model of circular-disk microcavity laser. We show that a small hole can enhance the directionality greatly and leave the threshold gain intact, if disk's refractive index is large enough and hole's location is chosen properly. This location should be close to the area where the same uniform disk, if illuminated with a plane wave, displays a broadband focusing in the form of hot spot called photonic jet. © 2021 IEEE.

关键词： Refractive index

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Quantum Algorithmic Gate-Based Computing: Grover Quantum Search Algorithm Design in Quantum Software Engineering

arXiv

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arXiv 2023年

作者： Sergey, Ulyanov V. Viktor, Ulyanov S. Institute of System Analysis and Management Dubna State University Russia Meshcheryakov Laboratory of Information Technologies Joint Institute for Nuclear Research Russia Russia

The difference between classical and quantum algorithms (QA) is following: problem solved by QA is coded in the structure of the quantum operators. Input to QA in this case is always the same. Output of QA says which problem coded. In some sense, give a function to QA to analyze and QA returns its property as an answer without quantitative computing. QA studies qualitative properties of the functions. The core of any QA is a set of unitary quantum operators or quantum gates. In practical representation, quantum gate is a unitary matrix with particular structure. The size of this matrix grows exponentially with an increase in the number of inputs, which significantly limits the QA simulation on a classical computer with von Neumann architecture. Quantum search algorithm (QSA) - models apply for the solution of computer science problems as searching in unstructured data base, quantum cryptography, engineering tasks, control system design, robotics, smart controllers, etc. Grover’s algorithm is explained in details along with implementations on a local computer simulator. The presented article describes a practical approach to modeling one of the most famous QA on classical computers, the Grover *** Codes 81-08, 81-05, 68T40, 93C85 © 2023, CC BY.

关键词： Computer control systems

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Fast Quantum Search Algorithm Modelling on Conventional Computers: information analysis of Termination Problem

arXiv

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arXiv 2023年

作者： Ulyanov, Sergey V. Ulyanov, Viktor S. Institute of System Analysis and Management Dubna State University Russia Meshcheryakov Laboratory of Information Technologies Joint Institute for Nuclear Research Russia Russia

MSC Codes 81-08, 81-05, 68T40, 93C85,The simplest technique for simulating a quantum algorithm (QA) described based on the direct matrix representation of the quantum operators. This approach is stable and precise, but it requires allocation of operator’s matrices in the computer’s memory. Since the size of the operators grows exponentially, this approach is useful for simulation of QAs with a relatively small number of qubits (e.g., approximately 11 qubits on a typical desktop computer). Using this approach, it is relatively simple to simulate the operation of a QA and to perform fidelity analysis. A more efficient fast QA simulation technique is based on computing all or part of the operator matrices on an as needed current computational basis. Using this technique, it is possible to avoid storing all or part of the operator matrices. In this case, the number of qubits that can be simulated (e.g., the number of input qubits, or the number of qubits in the system state register) is affected by: (i) the exponential growth in the number of operations required to calculate the result of the matrix products;and (ii) the size of the state vector that is allocated in computer memory. In one embodiment, apply this approach it is reasonable to simulate up to 19 or more qubits on typical desktop computer, and even more on a system with vector architecture. Due to particularities of the memory addressing and access processes in a typical desktop computer (such as, for example, a Pentium-based Personal Computer), when the number of qubits is relatively small, the compute-on-demand approach tends to be faster than the direct storage approach. The compute-on-demand approach benefits from a study of the quantum operators, and their structure so that the matrix elements can be computed more efficiently. Effective simulation of Grover’s quantum search algorithm as example on computer with classical architecture is considered. © 2023, CC BY.

关键词： Personal computers

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Strong Time-Periodic Solutions to the 3d Oceanic Primitive Equations with the Gent-Mcwilliams-Redi Eddy Parametrization Model and Arbitrary Large Outer Forces

SSRN

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SSRN 2025年

作者： Zhang, Jie Liu, Wenjun School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing210044 China

To capture the effect of mesoscale eddies on oceanic temperature and salinity, we take the Gent-McWilliams-Redi eddy parametrization model into account in an ocean model with outer forces consisting of the 3D primitive equations and a set of advection-diffusion equations describing the oceanic tracers of temperature and salinity. The existence of strong time-periodic ($T$-periodic) solutions for this model is established under three time-periodic outer forces without any smallness conditions, provided that the density function for pressure, temperature and salinity satisfies the certain regularity assumption. Firstly, we prove the existence of a weak $T$-periodic solution relying on the Faedo-Galerkin method, Brouwer's fixed-point theorem and a priori bounds. Secondly, we prove the global well-posedness of strong solutions for arbitrary large outer forces and initial data that are in appropriately chosen function classes. Finally, we adopt the method of the weak-strong uniqueness to obtain a strong $T$-periodic solution for this model. © 2025, The Authors. All rights reserved.

关键词： Fixed point arithmetic

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Decision Tree Pruning Method Using Delayed Sampling 38

Decision Tree Pruning Method Using Delayed Sampling

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38th International Conference on information technologies, InfoTech 2024

作者： Mitrofanov, Sergei Alexandrovich Semenkin, Eugene Stanislavovich Reshetnev Siberian State University of Science and Technology Institute of Informatics and Telecommunications Department of System Analysis and Operations Research Krasnoyarsky Rabochy Av. 31 Krasnoyarsk Russia Bauman Moscow State Technical University Scientific and Educational Center "Artificial Intelligence Technologies" 2nd Baumanskaya St. 5 Moscow Russia Siberian Federal University Laboratory "Hybrid Methods of Modeling and Optimization in Complex Systems" Academic Kirensky St. 26a Krasnoyarsk Russia

ISBN: (纸本)9798350365689

Algorithms based on decision trees have been around for quite some time, however, they are still one of the most popular because of their efficiency and the interpretability of their results. One of the main problems of decision trees is their high tendency to overfit. There are various ways to solve this problem, but this paper proposes a new method based on tree pruning using delayed sampling. The tree is trained using the Separation Measure and Differential Evolution algorithms. The proposed approach improves the standard method and is compared with it. The proposed approach demonstrates higher efficiency than the standard algorithm, and also improves the interpretability of the resulting trees. © 2024 IEEE.

关键词： Adversarial machine learning

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Identification of soybean in Argentina using Sentinel-2 composite images

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International Journal of Agricultural and Biological Engineering 2024年第5期17卷 266-274页

作者： Linsheng Huang Yue Chen Yuhao Pan Zihang Lou Shijun Zheng Xiaoyang Zhang Le Yu Shengwei Liu Dailiang Peng National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefei 230601China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China Research Area of Ecology and Biodiversity School of Biological SciencesThe University of Hong KongPokfulamHong KongChina College of Environmental and Resource Sciences Zhejiang UniversityHangzhou 310058China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China Geospatial Sciences Center of Excellence Department of Geography&Geospatial SciencesSouth Dakota State UniversityBrookingsSD 57007USA Ministry of Education Ecological Field Station for East Asian Migratory Birds Beijing 100084China Tsinghua University(Department of Earth System Science)-Xi’an Institute of Surveying and Mapping Joint Research Center for Next-Generation Smart Mapping Beijing 100084China School of Surveying and Land Information Engineering Henan Polytechnic UniversityJiaozuo 454000HenanChina

Soybean is one of the most important oil crops, and Argentina is the third-largest soybean producer in the world, accounting for 17% of the global soybean yield. Timely and accurate information on soybean spatial distribution is critical for ensuring global food security. Sentinel-2 multispectral data and machine learning classification models are used to investigate the potential of soybean identification in the early stage of the growing season in Argentina, with the help of Google Earth Engine (GEE). The earliest time window and optimal feature set for soybean identification are explored. Results are as follows: 1) the random forest (RF) classification model demonstrated the highest level of classification accuracy compared to the backpropagation neural network (BPNN), support vector machine (SVM), and naive Bayes (NB) models;2) Soybean can be accurately identified as early as the end of February (filling stage), which is approximately one month before harvest;3) The optimal feature-subset can reduce the amount of input data by 80% while maintaining high classification accuracy. The overall accuracy (OA) of the RF classification model is 85.87%, and the relative error between the estimated soybean planting area and the agricultural statistics is 3.45%. This study provided a high-precision method for early-season identification of soybeans over large scales. The results can provide a data support for early futures trading and agricultural insurance, as well as a reference for policy-making to ensure global soybean food security.

关键词： soybean machine learning time window feature selection Sentinel-2 Google Earth Engine

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Graph Chirp Signal and Graph Fractional Vertex-Frequency Energy Distribution

arXiv

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arXiv 2025年

作者： Cui, Manjun Zhang, Zhichao School of Mathematics and Statistics The Center for Applied Mathematics of Jiangsu Province The Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing210044 China School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Computational Science and Application of Hainan Province Hainan Normal University Haikou571158 China

Graph signal processing (GSP) has emerged as a powerful framework for analyzing data on irregular domains. In recent years, many classical techniques in signal processing (SP) have been successfully extended to GSP. Among them, chirp signals play a crucial role in various SP applications. However, graph chirp signals have not been formally defined despite their importance. Here, we define graph chirp signals and establish a comprehensive theoretical framework for their analysis. We propose the graph fractional vertex-frequency energy distribution (GFED), which provides a powerful tool for processing and analyzing graph chirp signals. We introduce the general fractional graph distribution (GFGD), a generalized vertex-frequency distribution, and the reduced interference GFED, which can suppress cross-term interference and enhance signal clarity. Furthermore, we propose a novel method for detecting graph signals through GFED domain filtering, facilitating robust detection and analysis of graph chirp signals in noisy environments. Moreover, this method can be applied to real-world data for denoising more effective than some state-of-the-arts, further demonstrating its practical significance. Copyright © 2025, The Authors. All rights reserved.

关键词： Wiener filtering

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