.png){kind=icon}
返回
Nonlinear Audio Systems Identification Through Audio Input Gaussianization
.png){kind=icon}
OA
AI
DOI：10.1109/TASL.2013.2282214.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Nonlinear audio system identification generally relies on Gaussianity, whiteness and stationarity hypothesis on the input signal, although audio signals are non-Gaussian, highly correlated and non-stationary. However, since the physical behavior of nonlinear audio systems is input-dependent, they should be identified using natural audio signals (speech or music) as input, instead of artificial signals (sweeps or noise) as usually done. We propose an identification scheme that conditions audio signals to fit the desired properties for an efficient identification. The identification system consists in (1) a Gaussianization step that makes the signal nearGaussian under a perceptual constraint; (2) a predictor filterbank that whitens the signal; (3) an orthonormalization step that enhances the statistical properties of the input vector of the last step, under a Gaussianity hypothesis; (4) an adaptive nonlinear model. The proposed scheme enhances the convergence rate of the identification and reduces the steady state identification error, compared to other schemes, for example the classical adaptive nonlinear identification.
Keyword:
Audio gaussianization
nonlinear system identification
orthonormalization.
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
I
IF:
5.1
论文数:
2.6K
被引数:
1.1W
机构
引用论文
分享收藏Platelet function and prostaglandins in patients with peripheral vascular disease treated with calcium dobesilate钙 Dobesilate 治疗的周围血管疾病患者的血小板功能和前列腺素
PREAI
分享收藏Efficacy and safety of calcium dobesilate in patients with chronic venous insufficiency: an open-label, multicenter study钙 Dobesilate 在慢性静脉功能不全患者中的疗效和安全性：一项开放标签、多中心研究
PREAI
分享收藏Adaptation of a memoryless preprocessor for nonlinear acoustic echo cancelling.png)
SIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
分享收藏
查看更多内容