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Entropy-Based Volatility Analysis of Financial Log-Returns Using Gaussian Mixture Models. 使用高斯混合模型对金融对数收益率进行基于熵的波动性分析。
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-25 DOI: 10.3390/e26110907
Luca Scrucca
{"title":"Entropy-Based Volatility Analysis of Financial Log-Returns Using Gaussian Mixture Models.","authors":"Luca Scrucca","doi":"10.3390/e26110907","DOIUrl":"10.3390/e26110907","url":null,"abstract":"<p><p>Volatility in financial markets refers to the variation in asset prices over time. High volatility indicates increased risk, making its evaluation essential for effective risk management. Various methods are used to assess volatility, with the standard deviation of log-returns being a common approach. However, this implicitly assumes that log-returns follow a Gaussian distribution, which is not always valid. In this paper, we explore the use of (differential) entropy to evaluate the volatility of financial log-returns. Estimation of entropy is obtained using a Gaussian mixture model to approximate the underlying density of log-returns. Following this modeling approach, popular risk measures such as Value at Risk and Expected Shortfall can also be computed. By integrating Gaussian mixture modeling and entropy into the analysis of log-returns, we aim to provide a more accurate and robust framework for assessing financial volatility and risk measures.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11592438/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142727188","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
Random Walks and Lorentz Processes. 随机漫步与洛伦兹过程
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-25 DOI: 10.3390/e26110908
Domokos Szász
{"title":"Random Walks and Lorentz Processes.","authors":"Domokos Szász","doi":"10.3390/e26110908","DOIUrl":"10.3390/e26110908","url":null,"abstract":"<p><p>Random walks and Lorentz processes serve as fundamental models for Brownian motion. The study of random walks is a favorite object of probability theory, whereas that of Lorentz processes belongs to the theory of hyperbolic dynamical systems. Here we first present an example where the method based on the probabilistic approach led to new results for the Lorentz process: concretely, the recurrence of the planar periodic Lorentz process with a finite horizon. Afterwards, an unsolved problem-related to a 1981 question of Sinai on locally perturbed periodic Lorentz processes-is formulated as an analogous problem in the language of random walks.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11593204/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142727209","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
Bifurcations in a Model of Criminal Organizations and a Corrupt Judiciary. 犯罪组织和腐败司法机构模型中的分叉。
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-25 DOI: 10.3390/e26110906
G S Harari, L H A Monteiro
{"title":"Bifurcations in a Model of Criminal Organizations and a Corrupt Judiciary.","authors":"G S Harari, L H A Monteiro","doi":"10.3390/e26110906","DOIUrl":"10.3390/e26110906","url":null,"abstract":"<p><p>Let a population be composed of members of a criminal organization and judges of the judicial system, in which the judges can be co-opted by this organization. In this article, a model written as a set of four nonlinear differential equations is proposed to investigate this population dynamics. The impact of the rate constants related to judges' co-optation and ex-convicts' recidivism on the population composition is explicitly examined. This analysis reveals that the proposed model can experience backward and transcritical bifurcations. Also, if all ex-convicts relapse, organized crime cannot be eradicated even in the absence of corrupt judges. The results analytically derived here are illustrated by numerical simulations and discussed from a crime-control perspective.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11593032/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142727051","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
Quantum Machine Learning-Quo Vadis? 量子机器学习--何去何从？
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-24 DOI: 10.3390/e26110905
Andreas Wichert
{"title":"Quantum Machine Learning-Quo Vadis?","authors":"Andreas Wichert","doi":"10.3390/e26110905","DOIUrl":"10.3390/e26110905","url":null,"abstract":"<p><p>The book <i>Quantum Machine Learning: What Quantum Computing Means to Data Mining</i>, by Peter Wittek, made quantum machine learning popular to a wider audience. The promise of quantum machine learning for big data is that it will lead to new applications due to the exponential speed-up and the possibility of compressed data representation. However, can we really apply quantum machine learning for real-world applications? What are the advantages of quantum machine learning algorithms in addition to some proposed artificial problems? Is the promised exponential or quadratic speed-up realistic, assuming that real quantum computers exist? Quantum machine learning is based on statistical machine learning. We cannot port the classical algorithms directly into quantum algorithms due to quantum physical constraints, like the input-output problem or the normalized representation of vectors. Theoretical speed-ups of quantum machine learning are usually analyzed in the literature by ignoring the input destruction problem, which is the main bottleneck for data encoding. The dilemma results from the following question: should we ignore or marginalize those constraints or not?</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11592775/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142727200","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
Image Forensics in the Encrypted Domain. 加密领域的图像取证。
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-24 DOI: 10.3390/e26110900
Yongqiang Yu, Yuliang Lu, Longlong Li, Feng Chen, Xuehu Yan
{"title":"Image Forensics in the Encrypted Domain.","authors":"Yongqiang Yu, Yuliang Lu, Longlong Li, Feng Chen, Xuehu Yan","doi":"10.3390/e26110900","DOIUrl":"10.3390/e26110900","url":null,"abstract":"<p><p>Encryption techniques used by forgers have thrown out a big possible challenge to forensics. Most traditional forensic tools will fail to detect the forged multimedia, which has been encrypted. Thus, image forensics in the encrypted domain (IFED) is significant. This paper presents the first introduction of IFED, encompassing its problem description, formal definition, and evaluation metrics. The focus then turns to the challenge of detecting copy-move alterations in the encrypted domain using the classic permutation encryption technique. To tackle this challenge, we introduce and develop a lightweight enhanced forensic network (LEFN) based on deep learning to facilitate automatic IFED. Extensive experiments and analyses were conducted to comprehensively validate the proposed scheme.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11593136/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142727225","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
Mapping Data to Concepts: Enhancing Quantum Neural Network Transparency with Concept-Driven Quantum Neural Networks. 将数据映射到概念：用概念驱动的量子神经网络增强量子神经网络的透明度。
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-24 DOI: 10.3390/e26110902
Jinkai Tian, Wenjing Yang
{"title":"Mapping Data to Concepts: Enhancing Quantum Neural Network Transparency with Concept-Driven Quantum Neural Networks.","authors":"Jinkai Tian, Wenjing Yang","doi":"10.3390/e26110902","DOIUrl":"10.3390/e26110902","url":null,"abstract":"<p><p>We introduce the concept-driven quantum neural network (CD-QNN), an innovative architecture designed to enhance the interpretability of quantum neural networks (QNNs). CD-QNN merges the representational capabilities of QNNs with the transparency of self-explanatory models by mapping input data into a human-understandable concept space and making decisions based on these concepts. The algorithmic design of CD-QNN is comprehensively analyzed, detailing the roles of the concept generator, feature extractor, and feature integrator in improving and balancing model expressivity and interpretability. Experimental results demonstrate that CD-QNN maintains high predictive accuracy while offering clear and meaningful explanations of its decision-making process. This paradigm shift in QNN design underscores the growing importance of interpretability in quantum artificial intelligence, positioning CD-QNN and its derivative technologies as pivotal in advancing reliable and interpretable quantum intelligent systems for future research and applications.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11592992/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142727196","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
A Fisher Information Theory of Aesthetic Preference for Complexity. 复杂性审美偏好的费雪信息理论
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-24 DOI: 10.3390/e26110901
Sébastien Berquet, Hassan Aleem, Norberto M Grzywacz
{"title":"A Fisher Information Theory of Aesthetic Preference for Complexity.","authors":"Sébastien Berquet, Hassan Aleem, Norberto M Grzywacz","doi":"10.3390/e26110901","DOIUrl":"10.3390/e26110901","url":null,"abstract":"<p><p>When evaluating sensory stimuli, people tend to prefer those with not too little or not too much complexity. A recent theoretical proposal for this phenomenon is that preference has a direct link to the Observed Fisher Information that a stimulus carries about the environment. To make this theory complete, one must specify the model that the brain has about complexities in the world. Here, we develop this model by first obtaining the distributions of three indices of complexity measured as normalized Shannon Entropy in real-world images from seven environments. We then search for a parametric model that accounts for these distributions. Finally, we measure the Observed Fisher Information that each image has about the parameters of this model. The results show that with few exceptions, the distributions of image complexities are unimodal, have negative skewness, and are leptokurtotic. Moreover, the sign and magnitude of the skewness varies systematically with the location of the mode. After investigating tens of models for these distributions, we show that the Logit-Losev function, a generalization of the hyperbolic-secant distribution, fits them well. The Observed Fisher Information for this model shows the inverted-U-shape behavior of complexity preference. Finally, we discuss ways to test our Fisher-Information theory.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11593017/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142726621","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
Stealthy Vehicle Adversarial Camouflage Texture Generation Based on Neural Style Transfer. 基于神经风格转移的隐形车辆对抗性伪装纹理生成。
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-24 DOI: 10.3390/e26110903
Wei Cai, Xingyu Di, Xin Wang, Weijie Gao, Haoran Jia
{"title":"Stealthy Vehicle Adversarial Camouflage Texture Generation Based on Neural Style Transfer.","authors":"Wei Cai, Xingyu Di, Xin Wang, Weijie Gao, Haoran Jia","doi":"10.3390/e26110903","DOIUrl":"10.3390/e26110903","url":null,"abstract":"<p><p>Adversarial attacks that mislead deep neural networks (DNNs) into making incorrect predictions can also be implemented in the physical world. However, most of the existing adversarial camouflage textures that attack object detection models only consider the effectiveness of the attack, ignoring the stealthiness of adversarial attacks, resulting in the generated adversarial camouflage textures appearing abrupt to human observers. To address this issue, we propose a style transfer module added to an adversarial texture generation framework. By calculating the style loss between the texture and the specified style image, the adversarial texture generated by the model is guided to have good stealthiness and is not easily detected by DNNs and human observers in specific scenes. Experiments have shown that in both the digital and physical worlds, the vehicle full coverage adversarial camouflage texture we create has good stealthiness and can effectively fool advanced DNN object detectors while evading human observers in specific scenes.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11592712/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142727241","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
On the Scaling of Transport Phenomena at a Monotonously Changing Hydraulic Conductivity Field. 论单调变化的水力传导场中的输运现象缩放。
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-24 DOI: 10.3390/e26110904
Yaniv Edery, Shaul Sorek
{"title":"On the Scaling of Transport Phenomena at a Monotonously Changing Hydraulic Conductivity Field.","authors":"Yaniv Edery, Shaul Sorek","doi":"10.3390/e26110904","DOIUrl":"10.3390/e26110904","url":null,"abstract":"<p><p>Monotonously stratified porous medium, where the layered medium changes its hydraulic conductivity with depth, is present in various systems like tilled soil and peat formation. In this study, the flow pattern within a monotonously stratified porous medium is explored by deriving a non-dimensional number, Fhp, from the macroscopic Darcian-based flow equation. The derived Fhp theoretically classifies the flow equation to be hyperbolic or parabolic, according to the hydraulic head gradient length scale, and the hydraulic conductivity slope and mean. This flow classification is explored numerically, while its effect on the transport is explored by Lagrangian particle tracking (LPT). The numerical simulations show the transition from hyperbolic to parabolic flow, which manifests in the LPT transition from advective to dispersive transport. This classification is also applied to an interpolation of tilled soil from the literature, showing that, indeed, there is a transition in the transport. These results indicate that in a monotonously stratified porous medium, very low conducting (impervious) formations may still allow unexpected contamination leakage, specifically for the parabolic case. This classification of the Fhp to the flow and transport pattern provides additional insight without solving the flow or transport equation only by knowing the hydraulic conductivity distribution.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11593263/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142726878","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
Critical Points in the Noiseberg Achievable Region of the Gaussian Z-Interference Channel. 高斯 Z 干扰信道 Noiseberg 可实现区域的临界点。
IF 2.1 3区 物理与天体物理
Entropy Pub Date : 2024-10-23 DOI: 10.3390/e26110898
Max H M Costa, Chandra Nair, David Ng
{"title":"Critical Points in the Noiseberg Achievable Region of the Gaussian Z-Interference Channel.","authors":"Max H M Costa, Chandra Nair, David Ng","doi":"10.3390/e26110898","DOIUrl":"10.3390/e26110898","url":null,"abstract":"<p><p>The Gaussian signaling strategy with power control for the Gaussian Z-interference channel with weak interference is reviewed in this paper. In particular, we study the various communication strategies that may arise at various points of the capacity region and identify the locations of the phase transitions between the various strategies. The Gaussian Z-interference channel with weak interference is known to have two critical points in its capacity region, where the slope of the region shows a sudden change. They occur at the points of the unconditional maximum rate for one of the users and the maximum rate that can be accommodated by the other user. In this paper, we discuss additional critical points (locations of phase transitions) in the achievable region of this channel. These turn out to be second-order phase transitions, i.e., we do not observe a discontinuous slope in the achievable rate region, but there is a discontinuity in the second derivative of the rate contour of the achievable region. This review paper is mainly based on some of our ITA (Information Theory and Applications Workshop, UCSD, San Diego, CA, USA) papers since 2011.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"26 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11592807/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142727139","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
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