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基于Overcomplet ICA的声音压缩模型 被引量：3

Sound Compression Model Based on Overcomplete ICA
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摘要 独立成分分析(ICA)方法是近几年发展起来的一种新统计方法,旨在将所观测到的多维随机向量转换成统计上尽可能独立的成分。本文基于Overcomplete(过完备)ICA算法(SCO),提出了一种新的声音压缩模型。我们的实验实现了SCO的混合压缩与分离解压功能。 ICA is a statistical method for transforming an observed multidimensional random vector into components that are mutually independent as possible. In this paper we introduce Algebra ICA algorithm (AICA) which is the ef- ficient approach to solve Overcomplete ICA algorithm problem. Then we put forward a new sound compression struc- ture based on the Overcomplete ICA algorithm(SCO). Finally we present an experiment on sound signal compression and decompression.
作者 江宇闻 黄榕波 朱思铭
机构地区 中山大学数学系 广东药学院数学教研室
出处 《计算机科学》 CSCD 北大核心 2005年第4期97-98,128,共3页 Computer Science
基金 国家自然科学基金(10371135)
关键词 压缩模型 独立成分分析(ICA) 声音 ICA算法 统计方法 随机向量 实验实现 SCO 解压 Overcomplete ICA Sound compression
分类号 TP391 [自动化与计算机技术—计算机应用技术] TS805 [轻工技术与工程]
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参考文献11

  • 1Lewicki M S,Sejnowski T J. Learning Overcomplete Representations. Neural Computation, 1998
  • 2Lee T W,Lewicki M S,Giorlami M. Blind Source Separation of More Sourses Than Mixture Using Overcomplete Representations. IEEE Signal Processing Letters, 1999,6 (4): 87～ 90
  • 3Lewicki M S, Sejnowski T J. Learning nonlinear overcomplete representations for efficient coding
  • 4Theis F J,Lang E W. Formalization of the Two-Step Approach to Overcomplete BSS
  • 5Theis F J. A Geometric Algorithm For Overcomplete Linear ICA
  • 6Theis F J, Jung A, Puntonent C G, Land E W. Linear Geomatric ICA:Fundamentals and Algorithms. Neural Computation 2003,15:419～439
  • 7Theis F J. A Geometric Algorithm for Overcomplete ICA
  • 8Waheed K,Salem F M. Algebraic Independent Componenet Analysis: An Approach for Separation of Overcomplete Speech Mixtures. IEEE 2003. 775～780
  • 9Zhang L Q,Cichocki A,Amari S. Nature Gradient Algorithm for Blind Separation of Overdetemind Mixuture with Additive Noise
  • 10Scott, Chen ShaoBing, Donoho D L, Saunders M A. Atomic Dcomposition by Basis Pursuit

同被引文献27

  • 1李拥军,江宇闻,朱思铭.基于最短路径和自然梯度的过完备ICA算法[J].计算机工程,2006,32(15):16-18. 被引量：4
  • 2Lewicki M S, Sejnowski T J. Learning Overcomplete Representations. Neural Computation, 1998
  • 3Lee T-W, Lewicki M S, Giorlami M. Blind Source Separation of More Sourses Than Mixture Using Overcomplete Representations. IEEE Signal Processing Letters, 1999,6 (4): 87～ 90
  • 4Theis F J. A Geometric Algorithm For Overcomplete Linear ICA
  • 5Waheed K,Salem F M. Algebraic Independent Componenet Analysis: An Approach for Separation of Overcomplete Speech Mixtures. IEEE (2003) ,775～780
  • 6Scott,Chen S B,Donoho D L,Saunders M A. Atomic Dcomposition by Basis Pursuit
  • 7Olshausen B A, Field D J. Sparse Coding with an Overcomplete Basis Set: A Strategy Employed by VI?, Elsevier Science, 1997,37(23) :3311～3325
  • 8Bartlett M S. Face Recognition by Independent Component Analysis. IEEE Trans On Neural Networks,2002,13(6)
  • 9Vapnik V. The Nature of Statistic Learning Theory. Springer,New York, 1995
  • 10Davies M,Mitianoudis N. Simple mixture model for sparse overcomplete ICA. IEEE Proc.-Vis Image Signal Process, 2004, 151(1)

引证文献3

二级引证文献2

计算机科学
2005年 第4期

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