Entropy (Basel, Switzerland)最新文献

A Novel Drinking Category Detection Method Based on Wireless Signals and Artificial Neural Network. 一种基于无线信号和人工神经网络的新型酒类分类检测方法。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-21 DOI: 10.3390/e24111700

Jie Zhang, Zhongmin Wang, Kexin Zhou, Ruohan Bai

{"title":"A Novel Drinking Category Detection Method Based on Wireless Signals and Artificial Neural Network.","authors":"Jie Zhang, Zhongmin Wang, Kexin Zhou, Ruohan Bai","doi":"10.3390/e24111700","DOIUrl":"https://doi.org/10.3390/e24111700","url":null,"abstract":"With the continuous improvement of people’s health awareness and the continuous progress of scientific research, consumers have higher requirements for the quality of drinking. Compared with high-sugar-concentrated juice, consumers are more willing to accept healthy and original Not From Concentrated (NFC) juice and packaged drinking water. At the same time, drinking category detection can be used for vending machine self-checkout. However, the current drinking category systems rely on special equipment, which require professional operation, and also rely on signals that are not widely used, such as radar. This paper introduces a novel drinking category detection method based on wireless signals and artificial neural network (ANN). Unlike past work, our design relies on WiFi signals that are widely used in life. The intuition is that when the wireless signals propagate through the detected target, the signals arrive at the receiver through multiple paths and different drinking categories will result in distinct multipath propagation, which can be leveraged to detect the drinking category. We capture the WiFi signals of detected drinking using wireless devices; then, we calculate channel state information (CSI), perform noise removal and feature extraction, and apply ANN for drinking category detection. Results demonstrate that our design has high accuracy in detecting drinking category.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689324/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40484699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Scale Enhancement Pyramid Network for Small Object Detection from UAV Images. 基于尺度增强金字塔网络的无人机图像小目标检测。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-21 DOI: 10.3390/e24111699

Jian Sun, Hongwei Gao, Xuna Wang, Jiahui Yu

{"title":"Scale Enhancement Pyramid Network for Small Object Detection from UAV Images.","authors":"Jian Sun, Hongwei Gao, Xuna Wang, Jiahui Yu","doi":"10.3390/e24111699","DOIUrl":"https://doi.org/10.3390/e24111699","url":null,"abstract":"Object detection is challenging in large-scale images captured by unmanned aerial vehicles (UAVs), especially when detecting small objects with significant scale variation. Most solutions employ the fusion of different scale features by building multi-scale feature pyramids to ensure that the detail and semantic information are abundant. Although feature fusion benefits object detection, it still requires the long-range dependencies information necessary for small objects with significant scale variation detection. We propose a simple yet effective scale enhancement pyramid network (SEPNet) to address these problems. A SEPNet consists of a context enhancement module (CEM) and feature alignment module (FAM). Technically, the CEM combines multi-scale atrous convolution and multi-branch grouped convolution to model global relationships. Additionally, it enhances object feature representation, preventing features with lost spatial information from flowing into the feature pyramid network (FPN). The FAM adaptively learns offsets of pixels to preserve feature consistency. The FAM aims to adjust the location of sampling points in the convolutional kernel, effectively alleviating information conflict caused by the fusion of adjacent features. Results indicate that the SEPNet achieves an AP score of 18.9% on VisDrone, which is 7.1% higher than the AP score of state-of-the-art detectors RetinaNet achieves an AP score of 81.5% on PASCAL VOC.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689004/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40484698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Transversality Conditions for Geodesics on the Statistical Manifold of Multivariate Gaussian Distributions. 多元高斯分布统计流形上测地线的横截性条件。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-21 DOI: 10.3390/e24111698

Trevor Herntier, Adrian M Peter

引用次数: 3

Bearing Fault Diagnosis Method Based on RCMFDE-SPLR and Ocean Predator Algorithm Optimizing Support Vector Machine. 基于RCMFDE-SPLR和Ocean Predator算法优化支持向量机的轴承故障诊断方法。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-20 DOI: 10.3390/e24111696

Mingxiu Yi, Chengjiang Zhou, Limiao Yang, Jintao Yang, Tong Tang, Yunhua Jia, Xuyi Yuan

{"title":"Bearing Fault Diagnosis Method Based on RCMFDE-SPLR and Ocean Predator Algorithm Optimizing Support Vector Machine.","authors":"Mingxiu Yi, Chengjiang Zhou, Limiao Yang, Jintao Yang, Tong Tang, Yunhua Jia, Xuyi Yuan","doi":"10.3390/e24111696","DOIUrl":"https://doi.org/10.3390/e24111696","url":null,"abstract":"For the problem that rolling bearing fault characteristics are difficult to extract accurately and the fault diagnosis accuracy is not high, an unsupervised characteristic selection method of refined composite multiscale fluctuation-based dispersion entropy (RCMFDE) combined with self-paced learning and low-redundant regularization (SPLR) is proposed, for which the fault diagnosis is carried out by support vector machine (SVM) optimized by the marine predator algorithm (MPA). First, we extract the entropy characteristics of the bearings under different fault states by RCMFDE and the introduction of the fine composite multiscale coarse-grained method and fluctuation strategy improves the stability and estimation accuracy of the bearing characteristics; then, a novel dimensionality-reduction method, SPLR, is used to select better entropy characteristics, and the local flow structure of the fault characteristics is preserved and the redundancy is constrained by two regularization terms; finally, using the MPA-optimized SVM classifier by combining Levy motion and Eddy motion strategies, the preferred RCMFDE is fed into the MPA-SVM model for fault diagnosis, for which the obtained bearing fault diagnosis accuracy is 97.67%. The results show that the RCMFDE can effectively improve the stability and accuracy of the bearing characteristics, the SPLR-based low-dimensional characteristics can suppress the redundancy characteristics and improve the effectiveness of the characteristics, and the MPA-based adaptive SVM model solves the parameter randomness problem and, therefore, the proposed method has outstanding superiority.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688966/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40484696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Bifurcation and Entropy Analysis of a Chaotic Spike Oscillator Circuit Based on the S-Switch. 基于s开关的混沌尖峰振荡电路的分岔与熵分析。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-19 DOI: 10.3390/e24111693

Petr Boriskov, Andrei Velichko, Nikolay Shilovsky, Maksim Belyaev

{"title":"Bifurcation and Entropy Analysis of a Chaotic Spike Oscillator Circuit Based on the S-Switch.","authors":"Petr Boriskov, Andrei Velichko, Nikolay Shilovsky, Maksim Belyaev","doi":"10.3390/e24111693","DOIUrl":"https://doi.org/10.3390/e24111693","url":null,"abstract":"This paper presents a model and experimental study of a chaotic spike oscillator based on a leaky integrate-and-fire (LIF) neuron, which has a switching element with an S-type current-voltage characteristic (S-switch). The oscillator generates spikes of the S-switch in the form of chaotic pulse position modulation driven by the feedback with rate coding instability of LIF neuron. The oscillator model with piecewise function of the S-switch has resistive feedback using a second order filter. The oscillator circuit is built on four operational amplifiers and two field-effect transistors (MOSFETs) that form an S-switch based on a Schmitt trigger, an active RC filter and a matching amplifier. We investigate the bifurcation diagrams of the model and the circuit and calculate the entropy of oscillations. For the analog circuit, the \"regular oscillation-chaos\" transition is analysed in a series of tests initiated by a step voltage in the matching amplifier. Entropy values are used to estimate the average time for the transition of oscillations to chaos and the degree of signal correlation of the transition mode of different tests. Study results can be applied in various reservoir computing applications, for example, in choosing and configuring the LogNNet network reservoir circuits.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689857/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40482818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Fast Driving of a Particle in Two Dimensions without Final Excitation. 无最终激励的二维粒子快速驱动。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-19 DOI: 10.3390/e24111694

Xiao-Jing Lu, Mikel Palmero, Ion Lizuain, Juan Gonzalo Muga

引用次数: 1

Are Guessing, Source Coding and Tasks Partitioning Birds of A Feather? 猜测、源代码编码和任务是一丘之貉吗?

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-19 DOI: 10.3390/e24111695

M Ashok Kumar, Albert Sunny, Ashish Thakre, Ashisha Kumar, G Dinesh Manohar

引用次数: 4

A Hybrid Opinion Formation and Polarization Model. 一种混合意见形成与极化模型。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-19 DOI: 10.3390/e24111692

Baizhong Yang, Quan Yu, Yi Fan

{"title":"A Hybrid Opinion Formation and Polarization Model.","authors":"Baizhong Yang, Quan Yu, Yi Fan","doi":"10.3390/e24111692","DOIUrl":"https://doi.org/10.3390/e24111692","url":null,"abstract":"The last decade has witnessed a great number of opinion formation models that depict the evolution of opinions within a social group and make predictions about the evolution process. In the traditional formulation of opinion evolution such as the DeGroot model, an agent's opinion is represented as a real number and updated by taking a weighted average of its neighbour's opinions. In this paper, we adopt a hybrid representation of opinions that integrate both the discrete and continuous nature of an opinion. Basically, an agent has a 'Yes', 'Neutral' or 'No' opinion on some issues of interest and associates with its Yes opinion a support degree which captures how strongly it supports the opinion. With such a rich representation, not only can we study the evolution of opinion but also that of support degree. After all, an agent's opinion can stay the same but become more or less supportive of it. Changes in the support degree are progressive in nature and only a sufficient accumulation of such a progressive change will result in a change of opinion say from Yes to No. Hence, in our formulation, after an agent interacts with another, its support degree is either strengthened or weakened by a predefined amount and a change of opinion may occur as a consequence of such progressive changes. We carry out simulations to evaluate the impacts of key model parameters including (1) the number of agents, (2) the distribution of initial support degrees and (3) the amount of change of support degree changes in a single interaction. Last but not least, we present several extensions to the hybrid and progressive model which lead to opinion polarization.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689558/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40482817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spike Spectra for Recurrences. 递归的尖峰谱。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-18 DOI: 10.3390/e24111689

K Hauke Kraemer, Frank Hellmann, Mehrnaz Anvari, Jürgen Kurths, Norbert Marwan

引用次数: 1

Hybrid Beamforming Design for Self-Interference Cancellation in Full-Duplex Millimeter-Wave MIMO Systems with Dynamic Subarrays. 动态子阵列全双工毫米波MIMO系统中自干扰消除的混合波束形成设计。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-18 DOI: 10.3390/e24111687

Gengshan Wang, Zhijia Yang, Tierui Gong

{"title":"Hybrid Beamforming Design for Self-Interference Cancellation in Full-Duplex Millimeter-Wave MIMO Systems with Dynamic Subarrays.","authors":"Gengshan Wang, Zhijia Yang, Tierui Gong","doi":"10.3390/e24111687","DOIUrl":"https://doi.org/10.3390/e24111687","url":null,"abstract":"Full-duplex (FD) millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication is a promising solution for the extremely high-throughput requirements in future cellular systems. The hybrid beamforming structure is preferable for its low hardware complexity and low power consumption with acceptable performance. In this paper, we introduce the hardware efficient dynamic subarrays to the FD mmWave MIMO systems and propose an effective hybrid beamforming design to cancel the self-interference (SI) in the considered system. First, assuming no SI, we obtain the optimal fully digital beamformers and combiners via the singular value decomposition of the uplink and downlink channels and the water-filling power allocation. Then, based on the obtained fully digital solutions, we get the dynamic analog solutions and digital solutions using the Kuhn-Munkres algorithm-aided dynamic hybrid beamforming design. Finally, we resort to the null space projection method to cancel the SI by projecting the obtained digital beamformer at the base station onto the null space of the equivalent SI channel. We further analyze the computational complexity of the proposed method. Numerical results demonstrate the superiority of the FD mmWave MIMO systems with the dynamic subarrays using the proposed method compared to the systems with the fixed subarrays and the half-duplex mmWave communications. When the number of RF chains is 6 and the signal-to-noise ratio is 10 dB, the proposed design outperforms the FD mmWave MIMO systems with fixed subarrays and the half-duplex mmWave communications, respectively, by 22.4% and 47.9% in spectral efficiency and 19.9% and 101% in energy efficiency.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689759/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40482812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1