DocumentCode
180563
Title
Monte Carlo limit cycle characterization
Author
Luengo, D. ; Oses, David ; Martino, Luca
Author_Institution
Dept. of Circuits & Sytems Eng., Univ. Politec. de Madrid, Madrid, Spain
fYear
2014
fDate
4-9 May 2014
Firstpage
8043
Lastpage
8047
Abstract
The fixed point implementation of IIR digital filters usually leads to the appearance of zero-input limit cycles, which degrade the performance of the system. In this paper, we develop an efficient Monte Carlo algorithm to detect and characterize limit cycles in fixed-point IIR digital filters. The proposed approach considers filters formulated in the state space and is valid for any fixed point representation and quantization function. Numerical simulations on several high-order filters, where an exhaustive search is unfeasible, show the effectiveness of the proposed approach.
Keywords
IIR filters; Monte Carlo methods; limit cycles; quantisation (signal); state-space methods; Monte Carlo algorithm; Monte Carlo limit cycle characterization; fixed point implementation; fixed point representation; fixed-point IIR digital filters; high-order filters; quantization function; state space; zero-input limit cycles; Limit-cycles; Monte Carlo methods; Passband; Proposals; Quantization (signal); Signal processing algorithms; IIR filters; Monte Carlo methods; finite wordlength effects; limit cycles;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6855167
Filename
6855167
Link To Document