EntropyPub Date : 2025-04-21DOI: 10.3390/e27040451
Xiuli Ji, Qian Wang, Liping Qian, Pooi-Yuen Kam
{"title":"Mutual Information Neural-Estimation-Driven Constellation Shaping Design and Performance Analysis.","authors":"Xiuli Ji, Qian Wang, Liping Qian, Pooi-Yuen Kam","doi":"10.3390/e27040451","DOIUrl":"https://doi.org/10.3390/e27040451","url":null,"abstract":"<p><p>The choice of constellations largely affects the performance of both wireless and optical communications. To address increasing capacity requirements, constellation shaping, especially for high-order modulations, is imperative in high-speed coherent communication systems. This paper, thus, proposes novel mutual information neural estimation (MINE)-based geometric, probabilistic, and joint constellation shaping schemes, i.e., the MINE-GCS, MINE-PCS, and MINE-JCS, to maximize mutual information (MI) via emerging deep learning (DL) techniques. Innovatively, we first introduce the MINE module to effectively estimate and maximize MI through backpropagation, without clear knowledge of the channel state information. Then, we train encoder and probability generator networks with different signal-to-noise ratios to optimize the distribution locations and probabilities of the points, respectively. Note that MINE transforms the precise MI calculation problem into a parameter optimization problem. Our MINE-based schemes only optimize the transmitter end, and avoid the computational and structural complexity in traditional shaping. All the designs were verified through simulations as having superior performance for MI, among which the MINE-JCS undoubtedly performed the best for additive white Gaussian noise, compared to the unshaped QAMs and even the end-to-end training and other DL-based joint shaping schemes. For example, the low-order 8-ary MINE-GCS could achieve an MI gain of about 0.1 bits/symbol compared to the unshaped Star-8QAM. It is worth emphasizing that our proposed schemes achieve a balance between implementation complexity and MI performance, and they are expected to be applied in various practical scenarios with different noise and fading levels in the future.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12025961/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143964347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
EntropyPub Date : 2025-04-21DOI: 10.3390/e27040450
Micaela Suriano, Leonidas Facundo Caram, Cesar Caiafa, Hernán Daniel Merlino, Osvaldo Anibal Rosso
{"title":"Information Theory Quantifiers in Cryptocurrency Time Series Analysis.","authors":"Micaela Suriano, Leonidas Facundo Caram, Cesar Caiafa, Hernán Daniel Merlino, Osvaldo Anibal Rosso","doi":"10.3390/e27040450","DOIUrl":"https://doi.org/10.3390/e27040450","url":null,"abstract":"<p><p>This paper investigates the temporal evolution of cryptocurrency time series using information measures such as complexity, entropy, and Fisher information. The main objective is to differentiate between various levels of randomness and chaos. The methodology was applied to 176 daily closing price time series of different cryptocurrencies, from October 2015 to October 2024, with more than 30 days of data and not completely null. Complexity-entropy causality plane (CECP) analysis reveals that daily cryptocurrency series with lengths of two years or less exhibit chaotic behavior, while those longer than two years display stochastic behavior. Most longer series resemble colored noise, with the parameter <i>k</i> varying between 0 and 2. Additionally, Natural Language Processing (NLP) analysis identified the most relevant terms in each white paper, facilitating a clustering method that resulted in four distinct clusters. However, no significant characteristics were found across these clusters in terms of the dynamics of the time series. This finding challenges the assumption that project narratives dictate market behavior. For this reason, investment recommendations should prioritize real-time informational metrics over whitepaper content.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12027155/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143973475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
EntropyPub Date : 2025-04-21DOI: 10.3390/e27040448
Mark A Gannon
{"title":"A Snapshot of Bayesianism.","authors":"Mark A Gannon","doi":"10.3390/e27040448","DOIUrl":"https://doi.org/10.3390/e27040448","url":null,"abstract":"<p><p>Students are told in basic probability classes that there are two main \"schools\" of statistics, the frequentist and the Bayesian, and that those different views of how to approach statistical inference problems arise from two different views of the meaning of probability [...].</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12026281/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143959366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
EntropyPub Date : 2025-04-21DOI: 10.3390/e27040449
Yasuji Sawada, Yasukazu Daigaku, Kenji Toma
{"title":"Maximum Entropy Production Principle of Thermodynamics for the Birth and Evolution of Life.","authors":"Yasuji Sawada, Yasukazu Daigaku, Kenji Toma","doi":"10.3390/e27040449","DOIUrl":"https://doi.org/10.3390/e27040449","url":null,"abstract":"<p><p>Research on the birth and evolution of life are reviewed with reference to the maximum entropy production principle (MEPP). It has been shown that this principle is essential for consistent understanding of the birth and evolution of life. First, a recent work for the birth of a self-replicative system as pre-RNA life is reviewed in relation to the MEPP. A critical condition of polymer concentration in a local system is reported by a dynamical system approach, above which, an exponential increase of entropy production is guaranteed. Secondly, research works of early stage of evolutions are reviewed; experimental research for the numbers of cells necessary for forming a multi-cellular organization, and numerical research of differentiation of a model system and its relation with MEPP. It is suggested by this review article that the late stage of evolution is characterized by formation of society and external entropy production. A hypothesis on the general route of evolution is discussed from the birth to the present life which follows the MEPP. Some examples of life which happened to face poor thermodynamic condition are presented with thermodynamic discussion. It is observed through this review that MEPP is consistently useful for thermodynamic understanding of birth and evolution of life, subject to a thermodynamic condition far from equilibrium.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12025891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143997041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
EntropyPub Date : 2025-04-21DOI: 10.3390/e27040447
Dobromir Dotov, Jingxian Gu, Philip Hotor, Joanna Spyra
{"title":"Analysis of High-Dimensional Coordination in Human Movement Using Variance Spectrum Scaling and Intrinsic Dimensionality.","authors":"Dobromir Dotov, Jingxian Gu, Philip Hotor, Joanna Spyra","doi":"10.3390/e27040447","DOIUrl":"https://doi.org/10.3390/e27040447","url":null,"abstract":"<p><p>Full-body movement involving multi-segmental coordination has been essential to our evolution as a species, but its study has been focused mostly on the analysis of one-dimensional data. The field is poised for a change by the availability of high-density recording and data sharing. New ideas are needed to revive classical theoretical questions such as the organization of the highly redundant biomechanical degrees of freedom and the optimal distribution of variability for efficiency and adaptiveness. In movement science, there are popular methods that up-dimensionalize: they start with one or a few recorded dimensions and make inferences about the properties of a higher-dimensional system. The opposite problem, dimensionality reduction, arises when making inferences about the properties of a low-dimensional manifold embedded inside a large number of kinematic degrees of freedom. We present an approach to quantify the smoothness and degree to which the kinematic manifold of full-body movement is distributed among embedding dimensions. The principal components of embedding dimensions are rank-ordered by variance. The power law scaling exponent of this variance spectrum is a function of the smoothness and dimensionality of the embedded manifold. It defines a threshold value below which the manifold becomes non-differentiable. We verified this approach by showing that the Kuramoto model obeys the threshold when approaching global synchronization. Next, we tested whether the scaling exponent was sensitive to participants' gait impairment in a full-body motion capture dataset containing short gait trials. Variance scaling was highest in healthy individuals, followed by osteoarthritis patients after hip replacement, and lastly, the same patients before surgery. Interestingly, in the same order of groups, the intrinsic dimensionality increased but the fractal dimension decreased, suggesting a more compact but complex manifold in the healthy group. Thinking about manifold dimensionality and smoothness could inform classic problems in movement science and the exploration of the biomechanics of full-body action.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12027049/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143983969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improving the Protection of Step-Down Transformers by Utilizing Percentage Differential Protection and Scale-Dependent Intrinsic Entropy.","authors":"Chia-Wei Huang, Chih-Chiang Fang, Wei-Tai Hsu, Chih-Chung Yang, Li-Ting Zhou","doi":"10.3390/e27040444","DOIUrl":"https://doi.org/10.3390/e27040444","url":null,"abstract":"<p><p>Transformer operations are susceptible to both internal and external faults. This study primarily employed software to construct a power system simulation model featuring a step-down transformer. The simulation model comprised three single-phase transformers with ten tap positions at the secondary coil to analyze internal faults. Additionally, ten fault positions between the power transformer and the load were considered for external fault analysis. The protection scheme incorporated percentage differential protection for both the power transformer and the transmission line, aiming to explore fault characteristics. To mitigate the protection device's sensitivity issues, the scale-dependent intrinsic entropy method was utilized as a decision support system to minimize power system protection misoperations. The results indicated the effectiveness and practicality of the auxiliary method through comprehensive failure analysis.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12025872/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143974541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
EntropyPub Date : 2025-04-20DOI: 10.3390/e27040446
Weilei Wen, Qianqian Zhao, Xiuli Shao
{"title":"MambaOSR: Leveraging Spatial-Frequency Mamba for Distortion-Guided Omnidirectional Image Super-Resolution.","authors":"Weilei Wen, Qianqian Zhao, Xiuli Shao","doi":"10.3390/e27040446","DOIUrl":"https://doi.org/10.3390/e27040446","url":null,"abstract":"<p><p>Omnidirectional image super-resolution (ODISR) is critical for VR/AR applications, as high-quality 360° visual content significantly enhances immersive experiences. However, existing ODISR methods suffer from limited receptive fields and high computational complexity, which restricts their ability to model long-range dependencies and extract global structural features. Consequently, these limitations hinder the effective reconstruction of high-frequency details. To address these issues, we propose a novel Mamba-based ODISR network, termed MambaOSR, which consists of three key modules working collaboratively for accurate reconstruction. Specifically, we first introduce a spatial-frequency visual state space model (SF-VSSM) to capture global contextual information via dual-domain representation learning, thereby enhancing the preservation of high-frequency details. Subsequently, we design a distortion-guided module (DGM) that leverages distortion map priors to adaptively model geometric distortions, effectively suppressing artifacts resulting from equirectangular projections. Finally, we develop a multi-scale feature fusion module (MFFM) that integrates complementary features across multiple scales, further improving reconstruction quality. Extensive experiments conducted on the SUN360 dataset demonstrate that our proposed MambaOSR achieves a 0.16 dB improvement in WS-PSNR and increases the mutual information by 1.99% compared with state-of-the-art methods, significantly enhancing both visual quality and the information richness of omnidirectional images.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12025934/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143974161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
EntropyPub Date : 2025-04-20DOI: 10.3390/e27040445
Sha Ye, Qiong Wu, Pingyi Fan, Qiang Fan
{"title":"A Survey on Semantic Communications in Internet of Vehicles.","authors":"Sha Ye, Qiong Wu, Pingyi Fan, Qiang Fan","doi":"10.3390/e27040445","DOIUrl":"https://doi.org/10.3390/e27040445","url":null,"abstract":"<p><p>The Internet of Vehicles (IoV), as the core of intelligent transportation system, enables comprehensive interconnection between vehicles and their surroundings through multiple communication modes, which is significant for autonomous driving and intelligent traffic management. However, with the emergence of new applications, traditional communication technologies face the problems of scarce spectrum resources and high latency. Semantic communication, which focuses on extracting, transmitting, and recovering some useful semantic information from messages, can reduce redundant data transmission, improve spectrum utilization, and provide innovative solutions to communication challenges in the IoV. This paper systematically reviews state-of-the-art semantic communications in the IoV, elaborates the technical background of the IoV and semantic communications, and deeply discusses key technologies of semantic communications in the IoV, including semantic information extraction, semantic communication architecture, resource allocation and management, and so on. Through specific case studies, it demonstrates that semantic communications can be effectively employed in the scenarios of traffic environment perception and understanding, intelligent driving decision support, IoV service optimization, and intelligent traffic management. Additionally, it analyzes the current challenges and future research directions. This survey reveals that semantic communications have broad application prospects in the IoV, but it is necessary to solve the real existing problems by combining advanced technologies to promote their wide application in the IoV and contributing to the development of intelligent transportation systems.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12027053/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143987683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
EntropyPub Date : 2025-04-19DOI: 10.3390/e27040441
Li Xie, Liangyan Li, Jun Chen, Lei Yu, Zhongshan Zhang
{"title":"A Constrained Talagrand Transportation Inequality with Applications to Rate-Distortion-Perception Theory.","authors":"Li Xie, Liangyan Li, Jun Chen, Lei Yu, Zhongshan Zhang","doi":"10.3390/e27040441","DOIUrl":"https://doi.org/10.3390/e27040441","url":null,"abstract":"<p><p>A constrained version of Talagrand's transportation inequality is established, which reveals an intrinsic connection between the Gaussian distortion-rate-perception functions with limited common randomness under the Kullback-Leibler divergence-based and squared Wasserstein-2 distance-based perception measures. This connection provides an organizational framework for assessing existing bounds on these functions. In particular, we show that the best-known bounds of Xie et al. are nonredundant when examined through this connection.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12025801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143993571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
EntropyPub Date : 2025-04-19DOI: 10.3390/e27040442
Yubin Li, Weida Zhan, Yichun Jiang, Jinxin Guo
{"title":"RDCRNet: RGB-T Object Detection Network Based on Cross-Modal Representation Model.","authors":"Yubin Li, Weida Zhan, Yichun Jiang, Jinxin Guo","doi":"10.3390/e27040442","DOIUrl":"https://doi.org/10.3390/e27040442","url":null,"abstract":"<p><p>RGB-thermal object detection harnesses complementary information from visible and thermal modalities to enhance detection robustness in challenging environments, particularly under low-light conditions. However, existing approaches suffer from limitations due to their heavy dependence on precisely registered data and insufficient handling of cross-modal distribution disparities. This paper presents RDCRNet, a novel framework incorporating a Cross-Modal Representation Model to effectively address these challenges. The proposed network features a Cross-Modal Feature Remapping Module that aligns modality distributions through statistical normalization and learnable correction parameters, significantly reducing feature discrepancies between modalities. A Cross-Modal Refinement and Interaction Module enables sophisticated bidirectional information exchange via trinity refinement for intra-modal context modeling and cross-attention mechanisms for unaligned feature fusion. Multiscale detection capability is enhanced through a Cross-Scale Feature Integration Module, improving detection performance across various object sizes. To overcome the inherent data scarcity in RGB-T detection, we introduce a self-supervised pretraining strategy that combines masked reconstruction with adversarial learning and semantic consistency loss, effectively leveraging both aligned and unaligned RGB-T samples. Extensive experiments demonstrate that RDCRNet achieves state-of-the-art performance on multiple benchmark datasets while maintaining high computational and storage efficiency, validating its superiority and practical effectiveness in real-world applications.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12027132/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143983970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}