Macro-adaptive algorithms
Abstract/Contents
- Abstract
- Traditionally, new adaptive algorithms were developed 'microscopically' by changing the internal structure of LMS, Recursive Least Squares (RLS) and their variants, such as update equations and optimization criteria. This research attempts to reignite the interest in improving adaptive algorithms by considering a different question: by treating any known adaptive algorithm as a black-box learning agent, what can we do to leverage these little learner(s) to form a more intelligent adaptive algorithm? A framework is developed in this thesis to guide the design process, in which algorithms created from the framework are only allowed to manipulate these little black-boxes without hacking into their inner workings. Since it is a block-level (macroscopic) design strategy, the framework is called 'Macro-Adaptive Framework' (MAF) and algorithms developed from the framework are called 'Macro-Adaptive Algorithms' (MAA), hence the name of the thesis. In this thesis, macro-adaptive framework (MAF) will be defined. Algorithms satisfying the framework, including new ones developed by the author, will be discussed, analyzed, and compared with other existing algorithms, followed by simulation results in adaptive system identification. Since MAF opened the flood-gate for aggressive optimization (squeezing more information out of limited number of samples) that was not previously available, one possible side effect is over-adaptation, which is rarely studied in adaptive filtering literature. In addition to solutions developed in the thesis, the author did some original research on the phenomenon and the results are presented in the thesis as well.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2014 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Wong, Hoi |
|---|---|
| Associated with | Stanford University, Department of Electrical Engineering. |
| Advisor | Widrow, Bernard, 1929- |
| Thesis advisor | Widrow, Bernard, 1929- |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Hoi Wong. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis (Engineering)--Stanford University, 2014. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2014 by Hoi Wong
Also listed in
Loading usage metrics...