{"title":"提高效率的一种改进的快速独立矢量分析算法","authors":"Dahu Wang, Chang Liu","doi":"10.1049/ell2.70246","DOIUrl":null,"url":null,"abstract":"<p>This paper proposes an improved fast independent vector analysis (FastIVA) algorithm. The proposed algorithm replaces the second-order derivative with the original function and its first derivative, incorporating an adaptive scaling factor to effectively reduce the number of iterations and computation time. The experiments are conducted based on a hybrid dataset constructed from the PNL Non-Speech Corpus and the ATR Japanese Speech Database. Experimental results demonstrate that the improved algorithm achieves separation performance comparable to the traditional FastIVA while significantly reducing both the iteration count and runtime.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70246","citationCount":"0","resultStr":"{\"title\":\"An Improved Fast Independent Vector Analysis Algorithm for Enhanced Efficiency\",\"authors\":\"Dahu Wang, Chang Liu\",\"doi\":\"10.1049/ell2.70246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper proposes an improved fast independent vector analysis (FastIVA) algorithm. The proposed algorithm replaces the second-order derivative with the original function and its first derivative, incorporating an adaptive scaling factor to effectively reduce the number of iterations and computation time. The experiments are conducted based on a hybrid dataset constructed from the PNL Non-Speech Corpus and the ATR Japanese Speech Database. Experimental results demonstrate that the improved algorithm achieves separation performance comparable to the traditional FastIVA while significantly reducing both the iteration count and runtime.</p>\",\"PeriodicalId\":11556,\"journal\":{\"name\":\"Electronics Letters\",\"volume\":\"61 1\",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2025-04-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70246\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronics Letters\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/ell2.70246\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics Letters","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/ell2.70246","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
An Improved Fast Independent Vector Analysis Algorithm for Enhanced Efficiency
This paper proposes an improved fast independent vector analysis (FastIVA) algorithm. The proposed algorithm replaces the second-order derivative with the original function and its first derivative, incorporating an adaptive scaling factor to effectively reduce the number of iterations and computation time. The experiments are conducted based on a hybrid dataset constructed from the PNL Non-Speech Corpus and the ATR Japanese Speech Database. Experimental results demonstrate that the improved algorithm achieves separation performance comparable to the traditional FastIVA while significantly reducing both the iteration count and runtime.
期刊介绍:
Electronics Letters is an internationally renowned peer-reviewed rapid-communication journal that publishes short original research papers every two weeks. Its broad and interdisciplinary scope covers the latest developments in all electronic engineering related fields including communication, biomedical, optical and device technologies. Electronics Letters also provides further insight into some of the latest developments through special features and interviews.
Scope
As a journal at the forefront of its field, Electronics Letters publishes papers covering all themes of electronic and electrical engineering. The major themes of the journal are listed below.
Antennas and Propagation
Biomedical and Bioinspired Technologies, Signal Processing and Applications
Control Engineering
Electromagnetism: Theory, Materials and Devices
Electronic Circuits and Systems
Image, Video and Vision Processing and Applications
Information, Computing and Communications
Instrumentation and Measurement
Microwave Technology
Optical Communications
Photonics and Opto-Electronics
Power Electronics, Energy and Sustainability
Radar, Sonar and Navigation
Semiconductor Technology
Signal Processing
MIMO