You are currently logged in as an
Institutional Subscriber.
If you would like to logout,
please click on the button below.
Home / Publications / E-library page
Only AES members and Institutional Journal Subscribers can download
In the field of audio signal processing, logarithmic frequency resolution IIR filters, such as fixed-pole parallel filters and Kautz filters, are often used. These proven structures can efficiently approximate the frequency resolution of hearing, which is a highly desired property in audio applications. In recursive adaptive filtering however, the FIR structure with LMS algorithm is the most common. Since the linear frequency resolution of FIR filters is not well-suited for audio applications, in this paper we explore the possibility of combining the logarithmic frequency resolution IIR filters with the LMS algorithm. To this end the LMS algorithm is applied to fixed-pole parallel and Kautz filters, and the resulting structures are compared in terms of convergence properties.
Author (s): Horváth, Kristóf; Bank, Balázs
Affiliation:
Budapest University of Technology and Economics
(See document for exact affiliation information.)
AES Convention: 148
Paper Number:10365
Publication Date:
2020-05-06
Import into BibTeX
Session subject:
Posters: Signal Processing
Permalink: https://aes2.org/publications/elibrary-page/?id=20782
(616KB)
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member Join the AES. If you need to check your member status, login to the Member Portal.
Horváth, Kristóf; Bank, Balázs; 2020; Comparison of LMS-based adaptive audio ?lters for identi?cation [PDF]; Budapest University of Technology and Economics; Paper 10365; Available from: https://aes2.org/publications/elibrary-page/?id=20782
Horváth, Kristóf; Bank, Balázs; Comparison of LMS-based adaptive audio ?lters for identi?cation [PDF]; Budapest University of Technology and Economics; Paper 10365; 2020 Available: https://aes2.org/publications/elibrary-page/?id=20782