Blind Identification Of Full-Sized Volterra Sysytems In SOS Domain

Author

Tan, Hong-Zhou ; Aboulnasr, Tyseer

Author_Institution

Sch. of Inf. Sci. & Technol., Sun Yat-Sen Univ., Guangzhou

Volume

2

fYear

2005

fDate

16-19 May 2005

Firstpage

900

Lastpage

903

Abstract

For a single-input single-output (SISO) Volterra system with finite order and memory, excited by unobservable i.i.d. stationary random sequences, it is known that subclasses of sparse Volterra systems are identifiable blindly in the second-order statistics (SOS) or higher-order statistics (HOS) domain under some conditions. In this paper, we show that, given sufficient conditions, a full-sized single-input multi-output (SIMO) Volterra system, structured by temporally or spatially oversampling its SISO counterpart, can be fully blindly identified in the SOS domain. Numerical simulations demonstrate the validity and usefulness of the proposed method

Keywords

Volterra series; higher order statistics; identification; signal sampling; blind identification; higher-order statistics domain; second-order statistics domain; single-input multioutput Volterra system; single-input single-output Volterra system; Higher order statistics; Information science; Information technology; Kernel; Nonlinear systems; Signal processing; Sparse matrices; Sufficient conditions; Sun; System identification; Blind identification; SIMO; SISO; Volterra systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2005. IMTC 2005. Proceedings of the IEEE

Conference_Location

Ottawa, Ont.

Print_ISBN

0-7803-8879-8

Type

conf

DOI

10.1109/IMTC.2005.1604265

Filename

1604265