Entropy最新文献_第6页

Hidden Markov Neural Networks.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-05 DOI: 10.3390/e27020168

Lorenzo Rimella, Nick Whiteley

引用次数: 0

The Nonlinear Dynamics and Chaos Control of Pricing Games in Group Robot Systems.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-04 DOI: 10.3390/e27020164

Chen Wang, Yi Sun, Ying Han, Chao Zhang

{"title":"The Nonlinear Dynamics and Chaos Control of Pricing Games in Group Robot Systems.","authors":"Chen Wang, Yi Sun, Ying Han, Chao Zhang","doi":"10.3390/e27020164","DOIUrl":"10.3390/e27020164","url":null,"abstract":"System stability control in resource allocation is a critical issue in group robot systems. Against this backdrop, this study investigates the nonlinear dynamics and chaotic phenomena that arise during pricing games among finitely rational group robots and proposes control strategies to mitigate chaotic behaviors. A system model and a business model for group robots are developed based on market mechanism mapping, and the dynamics of resource allocation are formulated as a second-order discrete nonlinear system using game theory. Numerical simulations reveal that small perturbations in system parameters, such as pricing adjustment speed, product demand coefficients, and resource substitution coefficients, can induce chaotic behaviors. To address these chaotic phenomena, a control method combining state feedback and parameter adjustment is proposed. This approach dynamically tunes the state feedback intensity of the system via a control parameter M, thereby delaying bifurcations and suppressing chaotic behaviors. It ensures that the distribution of system eigenvalues satisfies stability conditions, allowing control over unstable periodic orbits and period-doubling bifurcations. Simulation results demonstrate that the proposed control method effectively delays period-doubling bifurcations and stabilizes unstable periodic orbits in chaotic attractors. The stability of the system's Nash equilibrium is significantly improved, and the parameter range for equilibrium pricing is expanded. These findings provide essential theoretical foundations and practical guidance for the design and application of group robot systems.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 2","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854078/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143499839","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}

引用次数: 0

Fiducial Inference in Linear Mixed-Effects Models.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-03 DOI: 10.3390/e27020161

Jie Yang, Xinmin Li, Hongwei Gao, Chenchen Zou

引用次数: 0

Improved CNN Prediction Based Reversible Data Hiding for Images.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-03 DOI: 10.3390/e27020159

Yingqiang Qiu, Wanli Peng, Xiaodan Lin

引用次数: 0

Performance Improvement for Discretely Modulated Continuous-Variable Measurement-Device-Independent Quantum Key Distribution with Imbalanced Modulation.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-03 DOI: 10.3390/e27020160

Zehui Liu, Jiandong Bai, Fengchao Li, Yijun Li, Yan Tian, Wenyuan Liu

{"title":"Performance Improvement for Discretely Modulated Continuous-Variable Measurement-Device-Independent Quantum Key Distribution with Imbalanced Modulation.","authors":"Zehui Liu, Jiandong Bai, Fengchao Li, Yijun Li, Yan Tian, Wenyuan Liu","doi":"10.3390/e27020160","DOIUrl":"10.3390/e27020160","url":null,"abstract":"The modulation mode at the transmitters plays a crucial role in the continuous-variable measurement-device-independent quantum key distribution (CV-MDI-QKD) protocol. However, in practical applications, differences in the modulation schemes between two transmitters can inevitably impact protocol performance, particularly when using discrete modulation with four-state or eight-state formats. This work primarily investigates the effect of imbalanced modulation at the transmitters on the security of the CV-MDI-QKD protocol under both symmetric and asymmetric distance scenarios. By employing imbalanced discrete modulation maps and numerical convex optimization techniques, the proposed CV-MDI-QKD protocol achieves a notably higher secret key rate and outperforms existing protocols in terms of maximum transmission distance. Specifically, simulation results demonstrate that the secret key rate and maximum transmission distance are boosted by approximately 77.77% and 24.3%, respectively, compared to the original protocol. This novel and simplified modulation method can be seamlessly implemented in existing experimental setups without requiring equipment modifications. Furthermore, it provides a practical approach to enhancing protocol performance and enabling cost-effective applications in secure quantum communication networks under real-world environments.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 2","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11853792/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143500066","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}

引用次数: 0

PRG4CNN: A Probabilistic Model Checking-Driven Robustness Guarantee Framework for CNNs.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-03 DOI: 10.3390/e27020163

Yang Liu, Aohui Fang

{"title":"PRG4CNN: A Probabilistic Model Checking-Driven Robustness Guarantee Framework for CNNs.","authors":"Yang Liu, Aohui Fang","doi":"10.3390/e27020163","DOIUrl":"10.3390/e27020163","url":null,"abstract":"As an important kind of DNN (deep neural network), CNN (convolutional neural network) has made remarkable progress and been widely used in the vision and decision-making of autonomous robots. Nonetheless, in many scenarios, even a minor perturbation in input for CNNs may lead to serious errors, which means CNNs lack robustness. Formal verification is an effective method to guarantee the robustness of CNNs. Existing works predominantly concentrate on local robustness verification, which requires considerable time and space. Probabilistic robustness quantifies the robustness of CNNs, which is a practical mode of potential measurement. The state-of-the-art of probabilistic robustness verification is a test-driven approach, which is used to manually decide whether a DNN satisfies the probabilistic robustness and does not involve robustness repair. Robustness repair can improve the robustness of CNNs further. To address this issue, we propose a probabilistic model checking-driven robustness guarantee framework for CNNs, i.e., PRG4CNN. This is the first automated and complete framework for guaranteeing the probabilistic robustness of CNNs. It comprises four steps, as follows: (1) modeling a CNN as an MDP (Markov decision processes) by model learning, (2) specifying the probabilistic robustness of the CNN via the PCTL (Probabilistic Computational Tree Logic) formula, (3) verifying the probabilistic robustness with a probabilistic model checker, and (4) probabilistic robustness repair by counterexample-guided sensitivity analysis, if probabilistic robustness does not hold on the CNN. We here conduct experiments on various scales of CNNs trained on the handwriting dataset MNIST, and demonstrate the effectiveness of PRG4CNN.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 2","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854547/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143500068","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}

引用次数: 0

Unique Method for Prognosis of Risk of Depressive Episodes Using Novel Measures to Model Uncertainty Under Data Privacy.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-03 DOI: 10.3390/e27020162

Barbara Pękala, Dawid Kosior, Wojciech Rząsa, Katarzyna Garwol, Janusz Czuma

{"title":"Unique Method for Prognosis of Risk of Depressive Episodes Using Novel Measures to Model Uncertainty Under Data Privacy.","authors":"Barbara Pękala, Dawid Kosior, Wojciech Rząsa, Katarzyna Garwol, Janusz Czuma","doi":"10.3390/e27020162","DOIUrl":"10.3390/e27020162","url":null,"abstract":"The research described in this paper focuses on key aspects of learning from data concerning the symptoms of depression and how to prevent it. The computer support system designed for that purpose combines data privacy protection from various sources and uncertainty modeling, especially for incomplete data. The mentioned aspects are key to real-life medical diagnostic problems. From among the different paradigms of machine learning, a federated learning-based approach was chosen as the most suitable to take up the challenge. Importantly, computer support in medical diagnostics often requires algorithms that are appropriate for processing data expressing uncertainty and that can ensure high-quality diagnostics. To achieve this goal, a novel decision-making algorithm is used that employs interval entropy measures based on the theory of interval-valued fuzzy sets. Such an approach enables one to take into account diagnostic uncertainty, express it exactly, and interpret it easily. Furthermore, the applied classification technique offers the possibility of a straightforward explanation of the diagnosis, which is a situation required by many physicians. The presented solution combines innovative technological approaches with practical user needs, fostering the development of more effective tools in mental health prevention.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 2","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854257/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143499854","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}

引用次数: 0

Machine Learning Predictors for Min-Entropy Estimation.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-02 DOI: 10.3390/e27020156

Javier Blanco-Romero, Vicente Lorenzo, Florina Almenares Mendoza, Daniel Díaz-Sánchez

{"title":"Machine Learning Predictors for Min-Entropy Estimation.","authors":"Javier Blanco-Romero, Vicente Lorenzo, Florina Almenares Mendoza, Daniel Díaz-Sánchez","doi":"10.3390/e27020156","DOIUrl":"10.3390/e27020156","url":null,"abstract":"This study investigates the application of machine learning predictors for the estimation of min-entropy in random number generators (RNGs), a key component in cryptographic applications where accurate entropy assessment is essential for cybersecurity. Our research indicates that these predictors, and indeed any predictor that leverages sequence correlations, primarily estimate average min-entropy, a metric not extensively studied in this context. We explore the relationship between average min-entropy and the traditional min-entropy, focusing on their dependence on the number of target bits being predicted. Using data from generalized binary autoregressive models, a subset of Markov processes, we demonstrate that machine learning models (including a hybrid of convolutional and recurrent long short-term memory layers and the transformer-based GPT-2 model) outperform traditional NIST SP 800-90B predictors in certain scenarios. Our findings underscore the importance of considering the number of target bits in min-entropy assessment for RNGs and highlight the potential of machine learning approaches in enhancing entropy estimation techniques for improved cryptographic security.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 2","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854237/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143499987","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}

引用次数: 0

Protocells Either Synchronize or Starve.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-02 DOI: 10.3390/e27020154

Marco Villani, Roberto Serra

{"title":"Protocells Either Synchronize or Starve.","authors":"Marco Villani, Roberto Serra","doi":"10.3390/e27020154","DOIUrl":"10.3390/e27020154","url":null,"abstract":"Two different processes take place in self-reproducing protocells, i.e., (i) cell reproduction by fission and (ii) duplication of the genetic material. One major problem is indeed that of assuring that the two processes take place at the same pace, i.e., that they synchronize, which is a necessary condition for sustainable growth. In previous theoretical works, using dynamical models, we had shown that such synchronization can spontaneously emerge, generation after generation, under a broad set of hypotheses about the architecture of the protocell, the nature of the self-replicating molecules, and the types of kinetic equations. However, an important class of cases (quadratic or higher-order self-replication) did not synchronize in the models we had used, but could actually lead to divergence of the concentration of replicators. We show here that this behavior is due to a simplification of the previous models, i.e., the \"buffering\" hypothesis, which assumes instantaneous equilibrium of the internal and external concentrations of those compounds which can cross the cell membrane. That divergence disappears if we make use of more realistic dynamical models, with finite transmembrane diffusion rates of the precursors of replicators.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 2","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854096/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143500070","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}

引用次数: 0

Extending the QMM Framework to the Strong and Weak Interactions.

IF 2.1 3区物理与天体物理

Entropy Pub Date : 2025-02-02 DOI: 10.3390/e27020153

Florian Neukart, Eike Marx, Valerii Vinokur

{"title":"Extending the QMM Framework to the Strong and Weak Interactions.","authors":"Florian Neukart, Eike Marx, Valerii Vinokur","doi":"10.3390/e27020153","DOIUrl":"10.3390/e27020153","url":null,"abstract":"We extend the Quantum Memory Matrix (QMM) framework, originally developed to reconcile quantum mechanics and general relativity by treating space-time as a dynamic information reservoir, to incorporate the full suite of Standard Model gauge interactions. In this discretized, Planck-scale formulation, each space-time cell possesses a finite-dimensional Hilbert space that acts as a local memory, or quantum imprint, for matter and gauge field configurations. We focus on embedding non-Abelian SU(3)c (quantum chromodynamics) and SU(2)L × U(1)Y (electroweak interactions) into QMM by constructing gauge-invariant imprint operators for quarks, gluons, electroweak bosons, and the Higgs mechanism. This unified approach naturally enforces unitarity by allowing black hole horizons, or any high-curvature region, to store and later retrieve quantum information about color and electroweak charges, thereby preserving subtle non-thermal correlations in evaporation processes. Moreover, the discretized nature of QMM imposes a Planck-scale cutoff, potentially taming UV divergences and modifying running couplings at trans-Planckian energies. We outline major challenges, such as the precise formulation of non-Abelian imprint operators and the integration of QMM with loop quantum gravity, as well as possible observational strategies-ranging from rare decay channels to primordial black hole evaporation spectra-that could provide indirect probes of this discrete, memory-based view of quantum gravity and the Standard Model.","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 2","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854125/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143499906","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}

引用次数: 0