已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Identification of Room Acoustic Impulse Responses via Kronecker Product Decompositions

有限冲激响应 脉冲响应 计算机科学 克罗内克产品 脉冲(物理) 算法 维纳滤波器 混响 收敛速度 话筒 无限冲激响应 计算复杂性理论 自适应滤波器 系统标识 滤波器(信号处理) 数学 数字滤波器 克罗内克三角洲 声学 数学分析 计算机网络 频道(广播) 电信 物理 声压 量子力学 计算机视觉 数据库 度量(数据仓库)
作者
Laura-Maria Dogariu,Jacob Benesty,Constantin Paleologu,Silviu Ciochină
出处
期刊:IEEE/ACM transactions on audio, speech, and language processing [Institute of Electrical and Electronics Engineers]
卷期号:30: 2828-2841 被引量:18
标识
DOI:10.1109/taslp.2022.3202128
摘要

The identification of room acoustic impulse responses represents a challenging problem in the framework of many important applications related to the acoustic environment, like echo cancellation, noise reduction, and microphone arrays, among others. In this context, the main issues are related to the long length of such impulse responses and their time-variant nature. These raise significant difficulties in terms of the convergence rate, computational complexity, and accuracy of the solution. Recently, a decomposition-based approach was developed for the identification of low-rank systems, which can also be applied (to some extent) for the identification of acoustic impulse responses. This approach exploits the nearest Kronecker product decomposition of the impulse response and solves a high-dimension system identification problem using a combination of low-dimension solutions (provided by shorter filters), thus gaining in terms of both performance and complexity. Nevertheless, it does not consider the intrinsic nature of the room acoustic impulse responses, which contain specific components (e.g., early reflections and late reverberation) that can be very different in nature. In this paper, we propose an improved decomposition-based method (via the Kronecker product) that takes into account these specific components and processes them separately, in order to better exploit their important low-rank features. Following this approach, an iterative Wiener filter is firstly developed, followed by a recursive least-squares (RLS) algorithm designed in the same framework. Both solutions outperform the conventional benchmarks, i.e., the conventional Wiener filter and the RLS algorithm, respectively. Moreover, they achieve superior performances as compared to the recently developed versions based on the nearest Kronecker product decomposition, also owning lower computational complexities than their previous counterparts. Simulations are performed in the framework of acoustic echo cancellation and the obtained results support the performance features of the proposed algorithms.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
freebra发布了新的文献求助10
1秒前
冷面完成签到,获得积分10
2秒前
Charon完成签到,获得积分10
3秒前
polaris完成签到,获得积分10
3秒前
Meimei发布了新的文献求助10
4秒前
不安的晓灵完成签到 ,获得积分10
4秒前
4秒前
6秒前
自信向梦发布了新的文献求助10
6秒前
katu发布了新的文献求助10
6秒前
7秒前
pluto应助Becky采纳,获得10
9秒前
96完成签到 ,获得积分10
11秒前
yjihn发布了新的文献求助10
12秒前
杨晓慧完成签到 ,获得积分10
13秒前
FashionBoy应助从容黎昕采纳,获得10
14秒前
16秒前
Hazel完成签到 ,获得积分10
18秒前
赘婿应助清心采纳,获得10
18秒前
小马发布了新的文献求助10
19秒前
yeyongchang_hit完成签到,获得积分10
19秒前
科研通AI2S应助科研通管家采纳,获得50
19秒前
cc应助科研通管家采纳,获得10
20秒前
20秒前
zqh应助科研通管家采纳,获得50
20秒前
赘婿应助科研通管家采纳,获得10
21秒前
小二郎应助科研通管家采纳,获得10
21秒前
cc应助科研通管家采纳,获得10
21秒前
打打应助熊熊爱采纳,获得10
22秒前
FashionBoy应助NOV采纳,获得10
24秒前
逍遥自在完成签到,获得积分10
24秒前
24秒前
大方的香魔完成签到,获得积分10
26秒前
ppprotein发布了新的文献求助10
26秒前
juuui发布了新的文献求助10
28秒前
云云完成签到 ,获得积分10
29秒前
高大的雁菱完成签到,获得积分10
33秒前
林zp发布了新的文献求助10
33秒前
孜然味的拜拜肉完成签到,获得积分10
34秒前
逍遥自在发布了新的文献求助10
37秒前
高分求助中
Sustainability in ’Tides Chemistry 2000
Studien zur Ideengeschichte der Gesetzgebung 1000
The ACS Guide to Scholarly Communication 1000
TM 5-855-1(Fundamentals of protective design for conventional weapons) 1000
Handbook of the Mammals of the World – Volume 3: Primates 805
Ethnicities: Media, Health, and Coping 800
Gerard de Lairesse : an artist between stage and studio 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3072358
求助须知:如何正确求助?哪些是违规求助? 2726133
关于积分的说明 7492841
捐赠科研通 2373734
什么是DOI,文献DOI怎么找? 1258703
科研通“疑难数据库(出版商)”最低求助积分说明 610359
版权声明 596952