Title :
System identification utilizing adaptive filter with parallel structure
Author :
Kinjo, Shigenori ; Ochi, Hiroshi ; Yamada, Yoji
Author_Institution :
Ryukyus Univ., Okinawa, Japan
Abstract :
We propose a new scheme of subband adaptive digital filter(ADF) which allows massive parallel processing. We discuss the power spectral density of the down-sampled processes and propose a new cost function which is suitable for subband ADF. The subband scheme of adaptive system identification using the proposed cost function is considered. It is shown that we can carry out precise system identification based on the frequency domain sampling theorem, in which the proposed cost function is applied to the subband ADF using polyphase filter banks. The cost function is defined in each bin; as a result, it enables the perfect parallel processing of ADFs
Keywords :
adaptive filters; digital filters; filtering and prediction theory; identification; parallel processing; spectral analysis; FIR filter; adaptive system identification; cost function; down-sampled processes; frequency domain sampling theorem; massive parallel processing; parallel structure; polyphase filter banks; power spectral density; subband adaptive digital filter; Adaptive filters; Adaptive systems; Computational complexity; Cost function; Digital filters; Filter bank; Finite impulse response filter; Frequency; Frequency domain analysis; Parallel processing; Sampling methods; System identification;
Conference_Titel :
Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-4120-7
DOI :
10.1109/ACSSC.1993.342349
