NDLI: State space blind source recovery of non-minimum phase environments

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State space blind source recovery of non-minimum phase environments

Content Provider	IEEE Xplore Digital Library
Author	Waheed, K. Salarn, F.M.
Copyright Year	2002
Description	Author affiliation: Circuits, Syst. & Artificial Neural Networks Lab., Michigan State Univ., East Lansing, MI, USA (Waheed, K.; Salarn, F.M.)
Abstract	The paper describes the use of the state space and the natural gradient for the demixing of sources mixed in a non-minimum phase convolutive environment. Non-minimum phase implies that some or all of the zeros of the mixing environment lie outside the unit circle, and as such the theoretical inverse or the requisite demixing system becomes unstable due to the presence of poles outside the unit circle. These unstable poles are required to cancel out the non-minimum phase transmission zeros of the environment. In order to avoid instability due to the existence of these poles outside the unit circle, the natural gradient algorithm may be derived with the constraint that the demixing system is a double sided FIR filter, i.e., instead of trying to determine the IIR inverse of the environment, we approximate the inverse using an all zero non-causal filter. The use of the state space warrants that the derived framework is rich in structure while at the same time compact in representation. This results in derivation of update laws that can invariably handle most mixing scenarios. Some simulations illustrating the performance of the algorithm are also provided.
Sponsorship	IEEE Circuits & Syst. Soc. School of Electr. & Comput. Eng. at Oklahoma State Univ
File Size	232006
File Format	PDF
ISBN	0780375238
DOI	10.1109/MWSCAS.2002.1186888
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-08-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	State-space methods Finite impulse response filter Poles and zeros IIR filters Transfer functions Filtering Delay Vectors Circuits Artificial neural networks
Content Type	Text
Resource Type	Article

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