2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)最新文献_第9页

Direction-Sensitive Fast Measurement of Sub-Sampling-Period Delays 子采样周期时延的方向敏感快速测量

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9566042

J. Healy, M. Wan, J. Sheridan

引用次数: 2

Threshold Type Binary Memristor Emulator based on DVCC 基于DVCC的阈值型二进制忆阻器仿真器

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9565994

J. Roy, N. Pandey

引用次数: 0

Recognition Of Facial Expressions Using A Deep Neural Network 基于深度神经网络的面部表情识别

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9566065

Vipan Verma, Rajneesh Rani

引用次数: 0

Electronically Tunable Fractional Order Filter based on Single VDTA 基于单VDTA的电子可调谐分数阶滤波器

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9565975

Parveen Rani, R. Pandey

引用次数: 0

Epileptic seizure detection using STFT based peak mean feature and support vector machine 基于STFT的峰值均值特征和支持向量机的癫痫发作检测

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9566028

Nitin Sharma, Gaurav G, R. S. Anand

{"title":"Epileptic seizure detection using STFT based peak mean feature and support vector machine","authors":"Nitin Sharma, Gaurav G, R. S. Anand","doi":"10.1109/SPIN52536.2021.9566028","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566028","url":null,"abstract":"Epilepsy is a neurological condition of intermittent brain dysfunction arising from irregular neuronal discharge through the brain. The electroencephalogram (EEG) offers valuable information about the brain’s physiological states and is also an effective method for detecting epilepsy. This study aims to develop a computer-aided automation system to identify epileptic seizures through EEG data from epileptic and healthy subjects. We employed discrete Short-time Fourier transform (STFT) to decompose EEG data into sub-bands, and sample entropy, mean, and peak mean features were extracted from each sub-band. Feature ’mean’ accounts for baseline differences, ’sample entropy’ for the chaotic nature of EEG data, and ’peak mean’ for the amplitude differences between healthy and epileptic EEG data. We achieved the highest classification accuracy of 100% in distinguishing epileptic ictal EEG signals and EEG signals from healthy subjects through 10-fold cross-validation using the Support vector machine with radial basis function (SVM-RBF) classifier. We also presented the comparison of peak mean feature with other well-known features in epilepsy detection using EEG. The high accuracy results obtained by the peak mean feature show its potential in seizure detection using EEG.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130285858","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

Development of a Serious Game for the Purpose of Education and Learning 以教育和学习为目的的严肃游戏的开发

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9566120

Alok Rajpurohit, Aniket Raman, Hiral Modi

引用次数: 0

Low profile and low SAR flexible wearable patch antenna for WBAN 面向WBAN的低轮廓低SAR柔性可穿戴贴片天线

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9566096

Shivani Sharma, M. Tripathy, A. Sharma

引用次数: 0

Studying Electromagnetic field pattern for Breast Cancer Detection by Hexagonal Patch Antenna 六边形贴片天线检测乳腺癌的电磁场方向图研究

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9566129

Shruti Awasthi, P. Jain

引用次数: 1

A comparative Study to Predict the Property value using Machine Learning 利用机器学习预测房产价值的比较研究

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9566031

A. Shal, Richa Gupta

{"title":"A comparative Study to Predict the Property value using Machine Learning","authors":"A. Shal, Richa Gupta","doi":"10.1109/SPIN52536.2021.9566031","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566031","url":null,"abstract":"Estimating the value of a property in terms of money can be a very difficult challenge. A good estimation can help both buyer and seller and not also there is a huge demand for the models that can estimate the value of the property more precisely as it can be hugely helpful to avoid possible loss while trading in the property which is beneficial for both buyer and seller. Accordingly to solve this issue a lot of researchers have proposed a lot of Machine Learning and Deep Learning regression algorithms and models like Back Propagation Neural Network, Fuzzy Logic, Arima model, Multilevel Modelling, etc. Some of these models include some optimization or boosting techniques like Swarm optimization and Adaboost which help the model to give more precise results. Some of these previous models will be discussed further in this paper. To predict the property value with maximum effectiveness, we have conducted a comparative study of different Machine Learning Algorithms along with some attribute selection technique Partial Least Square Regression (PLSR), k-folds cross-validation, and pre-processing techniques to boost the accuracy of mentioned models. Hereby the performance will be evaluated on four parameters using the same dataset which will help us to compare the performance of each algorithm. These Four parameters are Average Profit or Loss, Adjusted R-Squared, Mean Absolute Error, and Mean Squared Error. Also, we have introduced a hybrid model to overcome the mentioned problem and this will be discussed further in this paper. Finally looking at the results obtained we can use the best algorithm to solve this problem. The algorithms used in this paper are Kernel Support Vector, XGBoost, and Decision Tree, ElasticNet, and a Hybrid regression model. According to the results obtained the Hybrid Regression model proposed by us is best for the estimation of property value.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121429459","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

A Modified-Zeta Converter based Onboard Battery Charging with Improved THD 基于改进THD的改进型zeta转换器车载电池充电

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) Pub Date : 2021-08-26 DOI: 10.1109/SPIN52536.2021.9566059

C. Chaudhary, Saurabh Mishra, U. Nangia

{"title":"A Modified-Zeta Converter based Onboard Battery Charging with Improved THD","authors":"C. Chaudhary, Saurabh Mishra, U. Nangia","doi":"10.1109/SPIN52536.2021.9566059","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566059","url":null,"abstract":"This paper presents onboard battery charging with a modified Zeta converter. Charging system is incorporated with two clamping diodes and two extra switches at Zeta converter input resulting in low THD input current and better charging efficiency by mitigating the problems of conventional Zeta converter. An AC-DC conversion is employed by diode bridge rectifier (DBR) followed by modified Zeta converter as power factor correction (PFC) unit, and the flyback converter is used to synchronize the current of battery with the implementation of closed loop cascaded PI control during constant voltage (CV) mode and constant current (CC) mode. Zeta converter is operated in Discontinuous conduction mode (DCM) mode such that Zeta converter can work with better dynamic response, and low ripple at the output voltage. Linear PI control topology is employed here, which has cascaded control for the better working efficiency of the charger. Proposed converter operation is to achieve low total harmonic distortion (THD) within IEC 61000-3-2 standards. Due to inbuilt isolation, components are less and hence proving the system to be more reliable. Proposed system’s efficacy is validated in MATLAB SIMULINK.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124342964","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: 3