DocumentCode :
2512164
Title :
Joint states dimension reduction and quantizer design for estimation under communication constraints
Author :
Ying, Shen ; Hui, Zhang
Author_Institution :
Dept. of Control Sci. & Eng., Zhejiang Univ., Hangzhou, China
fYear :
2011
fDate :
21-23 Oct. 2011
Firstpage :
390
Lastpage :
395
Abstract :
The problem of joint states dimension reduction and quantizer design under communication constraints was discussed for states estimation in quantized linear dynamic systems. In order to meet the requirements of transmit power constraint and the constraints of number and bandwidth of the parallel channels, the structure of DPCM (differential pulse code modulation) was adopted to produce the quantized innovation as the transmitted signal, and the states dimension reduction and quantizer were designed jointly under the MMSE (minimum mean square estimation error) criterion of filtering at receiver. Analytical analysis and simulation results show that, the estimation performance of the filter at receiver is optimal under communication constraints when the proposed dimension reduction method and the optimal quantizer are applied.
Keywords :
differential pulse code modulation; estimation theory; filtering theory; mean square error methods; quantisation (signal); state estimation; DPCM; MMSE; analytical analysis; analytical simulation; communication constraints estimation; differential pulse code modulation; dimension reduction method; filtering; joint states dimension reduction; minimum mean square estimation error criterion; optimal quantizer; parallel channels; performance estimation; quantized innovation; quantized linear dynamic systems; quantizer design; receiver; states estimation; transmit power constraint; transmitted signal; Bandwidth; Covariance matrix; Estimation error; Noise; Quantization; Technological innovation; bandwidth constraint; communication constraint; quantized linear system; states dimension reduction; transmit power constraint;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Problem-Solving (ICCP), 2011 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4577-0602-8
Electronic_ISBN :
978-1-4577-0601-1
Type :
conf
DOI :
10.1109/ICCPS.2011.6092294
Filename :
6092294
Link To Document :
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