| Publication Type |
Journal Article |
| School or College |
College of Engineering |
| Department |
Electrical & Computer Engineering |
| Creator |
Mathews, V. John |
| Title |
A fast recursive least-squares adaptive nonlinear filter |
| Date |
1988 |
| Description |
This paper presents a fast, recursive least-squares (RLS) adaptive nonlinear filter. The nonlinearity in the system is modeled using the Hammerstein model, which consists of a memoryless polynomial nonlinearity followed by a finite impulse response linear system. The complexity of our method is about 3NP2+7NP+N+10P2+6P multiplications per iteration and is substantially lower than the computational complexities of fast RLS algorithms that are direct extensions of RLS adaptive linear filters to the nonlinear case. |
| Type |
Text |
| Publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
| First Page |
156 |
| Last Page |
160 |
| Language |
eng |
| Bibliographic Citation |
Mathews, V. J. (1988). A fast recursive least-squares adaptive nonlinear filter. Proc. 21st Annual Asilomar Conf. Signals, Systems and Computers, 156-60. November. |
| Rights Management |
(c)1988 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
| Format Medium |
application/pdf |
| Format Extent |
651,938 bytes |
| Identifier |
ir-main,15132 |
| ARK |
ark:/87278/s6pg29bh |
| Setname |
ir_uspace |
| ID |
707087 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6pg29bh |
