Amirhossein Javaheri, Jiaxi Ying, Daniel P. Palomar, Farokh Marvasti
{"title":"重尾分布数据的时变图学习","authors":"Amirhossein Javaheri, Jiaxi Ying, Daniel P. Palomar, Farokh Marvasti","doi":"10.1109/tsp.2025.3588173","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"9 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time-Varying Graph Learning for Data with Heavy-Tailed Distribution\",\"authors\":\"Amirhossein Javaheri, Jiaxi Ying, Daniel P. Palomar, Farokh Marvasti\",\"doi\":\"10.1109/tsp.2025.3588173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":13330,\"journal\":{\"name\":\"IEEE Transactions on Signal Processing\",\"volume\":\"9 1\",\"pages\":\"\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1109/tsp.2025.3588173\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1109/tsp.2025.3588173","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
期刊介绍:
The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.