International Journal of Circuits, Systems and Signal Processing最新文献_第3页

Blockchain-Based Medical Cyber Physical Systems With Decentralized Threshold signature Scheme 基于区块链的分散式阈值签名方案医疗网络物理系统

International Journal of Circuits, Systems and Signal Processing Pub Date : 2023-03-06 DOI: 10.46300/9106.2023.17.7

Xianfei Zhou, Hongfang Cheng, Min Li, Fulong Chen

{"title":"Blockchain-Based Medical Cyber Physical Systems With Decentralized Threshold signature Scheme","authors":"Xianfei Zhou, Hongfang Cheng, Min Li, Fulong Chen","doi":"10.46300/9106.2023.17.7","DOIUrl":"https://doi.org/10.46300/9106.2023.17.7","url":null,"abstract":"Medical cyber physical systems are information applications of medical industry.A lagrge amount of medical data is stored in MCPS,and there are many challenges in the secure store and data sharing.Using blockchain technology into medical Cyber Physical system has become popular.Blockchain has remarkable features such as tamper proof and privacy protection, and has the function of protecting data in the medical Cyber Physical system.In this paper,we propose a hybrid blockchain,which applied private blockchain and consortium blockchain, After the medical source data is hashed, a hash tree is generated and stored in the private chain of the hospital. The hospital server extracts information to build a new transaction on the consortium chain.the system ensure the secure storage and fast access of data.Still,a threshold signature system is proposed.Aiming at the situation that medical accidents are easy to occur in multidisciplinary joint consultation in the medical process, this paper proposes to use threshold signature for joint consultation.Using the security and tamper-proof of the threshold signature, when the consensus is reached,treatment can be carried out and the medical data is uploaded to the consortium blockchain. The security analysis and performance analysis show that the scheme has advantages in safety and performance and is suitable for the medical environment.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90164921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Approach of Position and Torque Estimation for Induction Motor based Sensor-less Drive 基于感应电机无传感器驱动的位置和转矩估计方法

International Journal of Circuits, Systems and Signal Processing Pub Date : 2023-03-06 DOI: 10.46300/9106.2023.17.5

A. Ahriche

引用次数: 0

Adaptive Infinite Impulse Response System Identification Using Elitist Teaching-Learning- Based Optimization Algorithm 基于精英教-学优化算法的自适应无限脉冲响应系统辨识

International Journal of Circuits, Systems and Signal Processing Pub Date : 2023-03-03 DOI: 10.46300/9106.2023.17.1

Y. Ramalakshmanna, Dr. P. Shanmugaraja, D. V. R. Raju, Dr T.V. Hymalakshmi

{"title":"Adaptive Infinite Impulse Response System Identification Using Elitist Teaching-Learning- Based Optimization Algorithm","authors":"Y. Ramalakshmanna, Dr. P. Shanmugaraja, D. V. R. Raju, Dr T.V. Hymalakshmi","doi":"10.46300/9106.2023.17.1","DOIUrl":"https://doi.org/10.46300/9106.2023.17.1","url":null,"abstract":"Infinite Impulse Response (IIR) systems identification is complicated by traditional learning approaches. When reduced-order adaptive models are utilised for such identification, the performance suffers dramatically. The IIR system is identified as an optimization issue in this study. For system identification challenges, a novel population-based technique known as Elitist teacher learner-based optimization (ETLBO) is used to calculate the best coefficients of unknown infinite impulse response (IIR) systems. The MSE function is minimised and the optimal coefficients of an unknown IIR system are found in the system identification problem. The MSE is the difference between an adaptive IIR system's outputs and an unknown IIR system's outputs. For the unknown system coefficients of the same order and decreased order cases, exhaustive simulations have been performed. In terms of mean square error, convergence speed, and coefficient estimation, the results of actual and reduced-order identification for the standard system using the novel method outperform state-of-the-art techniques. For approximating the same-order and reduced-order IIR systems, four benchmark functions are examined utilizing GA, PSO, CSO, and BA. To demonstrate the improvements, the approach is evaluated on three conventional IIR systems of 2nd, 3rd, and 4th order models. On the basis of computing the mean square error (MSE) and fitness function, the suggested ETLBO approach for system identification is proven to be the best among others. Furthermore, it is confirmed that the suggested ETLBO method outperforms some of the other known system identification strategies. Finally, the efficiency of the dynamic nature of the control parameters of DE, TLBO, and BA in finding near parameter values of unknown systems is demonstrated through comparison data. The simulation results show that the suggested system identification approach outperforms the current methods for system identification.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76336558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unsupervised Deep Learning of Sparse Signals against Low-Rank Backgrounds with Application to Online Lung Sound Separation 低秩背景下稀疏信号的无监督深度学习在在线肺音分离中的应用

International Journal of Circuits, Systems and Signal Processing Pub Date : 2023-03-01 DOI: 10.18178/ijsps.11.1.1-6

引用次数: 0

Aliasing-Free and Additive Error in Mixed Spectra for Stable Processes. Application: Sound of a Bird just Captivated in Stress 稳定过程混合光谱中的无混叠误差和加性误差。应用:声音的鸟刚刚被困在压力

International Journal of Circuits, Systems and Signal Processing Pub Date : 2022-12-01 DOI: 10.18178/ijsps.10.4.18-24

R. Sabre

引用次数: 0

High Precision Low Input Voltage of 65nm CMOS Rectifier for Energy Harvesting using Threshold Voltage Minimization in Telemedicine Embedded System 基于阈值电压最小化的65nm CMOS整流器在远程医疗嵌入式系统中的高精度低输入电压采集

International Journal of Circuits, Systems and Signal Processing Pub Date : 2022-10-07 DOI: 10.46300/9106.2022.16.137

H. Fouad, Hesham Kamel, Adel Youssef

{"title":"High Precision Low Input Voltage of 65nm CMOS Rectifier for Energy Harvesting using Threshold Voltage Minimization in Telemedicine Embedded System","authors":"H. Fouad, Hesham Kamel, Adel Youssef","doi":"10.46300/9106.2022.16.137","DOIUrl":"https://doi.org/10.46300/9106.2022.16.137","url":null,"abstract":"Telemedicine applications run at very low input voltages, necessitating the use of Great Precision Rectifier with high sensitivity to function at low input voltages. In this study, we used a 65 nm CMOS rectifier to achieve a 0.2V input voltage for Energy Harvesting Telemedicine application. The suggested rectifier, which has two-stage structure and operates at frequency of 2.4GHz, has been found to perform better in cases where the minimum operating voltage is lower than previously published papers, and the rectifier can operate over a wide range of low input voltage amplitudes. Full-Wave Fully gate cross-coupled Rectifiers (FWFR) CMOS Rectifier Efficiency at Freq of 2.4 GHz: With an input voltage amplitude of 2V, the minimum and maximum output voltages are 0.49V and 1.997V, respectively, with a peak VCE of 99.85 percent and a peak PCE of 46.86 percent. This enables the suggested rectifier to be used in a variety of vibration energy collecting systems, including electrostatic, electromagnetic, and piezoelectric energy harvesters. The proposed rectifier, which is built at 2.4GHz and has a two-stage structure, performs better in the event of low input voltage amplitude and has lower minimum operation voltage than previously published papers. Full-wave fully gate cross-coupled rectifiers (FWFR) CMOS Rectifier Performance Summary at Freq of 2.4 GHz: With a 2V input voltage amplitude, the minimum and maximum output voltages are 0.49V and 1.997V, respectively, with a maximum VCE of 99.85% and a maximum PCE of 46.86%.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88390399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Compression of Hyper Spectral Images using Tensor Decomposition Methods 使用张量分解方法压缩高光谱图像

International Journal of Circuits, Systems and Signal Processing Pub Date : 2022-10-07 DOI: 10.46300/9106.2022.16.138

B. Sucharitha, D. Sheela

{"title":"Compression of Hyper Spectral Images using Tensor Decomposition Methods","authors":"B. Sucharitha, D. Sheela","doi":"10.46300/9106.2022.16.138","DOIUrl":"https://doi.org/10.46300/9106.2022.16.138","url":null,"abstract":"Tensor decomposition methods have beenrecently identified as an effective approach for compressing high-dimensional data. Tensors have a wide range of applications in numerical linear algebra, chemo metrics, data mining, signal processing, statics, and data mining and machine learning. Due to the huge amount of information that the hyper spectral images carry, they require more memory to store, process and send. We need to compress the hyper spectral images in order to reduce storage and processing costs. Tensor decomposition techniques can be used to compress the hyper spectral data. The primary objective of this work is to utilize tensor decomposition methods to compress the hyper spectral images. This paper explores three types of tensor decompositions: Tucker Decomposition (TD_ALS), CANDECOMP/PARAFAC (CP) and Tucker_HOSVD (Higher order singular value Decomposition) and comparison of these methods experimented on two real hyper spectral images: the Salinas image (512 x 217 x 224) and Indian Pines corrected (145 x 145 x 200). The PSNR and SSIM are used to evaluate how well these techniques work. When compared to the iterative approximation methods employed in the CP and Tucker_ALS methods, the Tucker_HOSVD method decomposes the hyper spectral image into core and component matrices more quickly. According to experimental analysis, Tucker HOSVD's reconstruction of the image preserves image quality while having a higher compression ratio than the other two techniques.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79351017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Effective Load Management for Grid Connected Hybrid Energy Sources 并网混合能源的有效负荷管理

International Journal of Circuits, Systems and Signal Processing Pub Date : 2022-09-19 DOI: 10.46300/9106.2022.16.136

C. Laxmi, Narendra Kumar, Rajendra Kumar Khad

{"title":"An Effective Load Management for Grid Connected Hybrid Energy Sources","authors":"C. Laxmi, Narendra Kumar, Rajendra Kumar Khad","doi":"10.46300/9106.2022.16.136","DOIUrl":"https://doi.org/10.46300/9106.2022.16.136","url":null,"abstract":"This paper introduces to control a standalone hybrid renewable system, involving PV cell and wind turbines as the primary energy sources along with fuel cell and battery energy source as an emotionally supportive system. While trying to work on the solidness and security of the hybrid renewable system sustainable framework, a battery bank, is incorporated as supporting units, due to the discontinuous and fluctuation in primary energy sources commitment. In this paper we model an independent sustainable source micro grid with various sources, which are wind energy with PMSG, PV panel, Fuel cell and battery storage system. Analysis of each source is done under variation conditions and variation of source parameters, such as wind speed of wind turbine, illumination, temperature of PV cell and state of charge of the battery. If main power sources of PV panel and wind turbines is not available, the battery storage device act as backup supply for load. This storage source (battery) can be charged when abundance power is produced from the PV panel and wind generation system. Investigation on each sources with dynamic changes of boundaries are studied with siumulation results analysis is studied by utilizing MATLAB/ SIMULINK software.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84307165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leakage Detection and Localization of Water Pipeline Using Multi-features and Adaptive Time Delay Estimation 基于多特征和自适应时滞估计的管道泄漏检测与定位

International Journal of Circuits, Systems and Signal Processing Pub Date : 2022-09-16 DOI: 10.46300/9106.2022.16.135

Yang Liu, Ze Chen, Zhongyan Liu, Xin Liu, Guochen Yu, Shun Na

{"title":"Leakage Detection and Localization of Water Pipeline Using Multi-features and Adaptive Time Delay Estimation","authors":"Yang Liu, Ze Chen, Zhongyan Liu, Xin Liu, Guochen Yu, Shun Na","doi":"10.46300/9106.2022.16.135","DOIUrl":"https://doi.org/10.46300/9106.2022.16.135","url":null,"abstract":"The leakage of water in pipelines severely affects the environment and economy. However, there are limitations in the effectiveness of existing leak detection and localization techniques and methodologies. In this paper, we propose a novel leakage detection and localization method based on the multiple time-frequency features, a neural network, and an adaptive time delay estimation algorithm. First, we use spectral subtraction and wavelet denoising to reduce the effects of noise. In addition, to ensure and improve the accuracy of leakage detection in complex realistic environments, we propose the use of multi time-frequency features that can comprehensively represent the leak signal and make the neural network more robust to train a radial basis function (RBF)neural network to detect the leak signal. Further, we extract multiple features of the leakage signal and input into the RBF neural network to train. Moreover, to prevent the impulsive components of environmental noise and improve localization accuracy, we further propose the use of a fractional lower-order statistics (FLOS) based adaptive time delay estimation algorithm to estimate the time delay and locate the leakage. The simulation results show that the detection and localization performance of the proposed method is superior to those of existing schemes.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74349364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recapitulation of Synthetic ECG Signal Generation methods and Analysis 合成心电信号生成方法综述及分析

International Journal of Circuits, Systems and Signal Processing Pub Date : 2022-09-01 DOI: 10.18178/ijsps.10.3.14-17

引用次数: 1