Null Space Projection Enhanced LMS Filters
| Autor: | Thomas Paireder, Michael Lunglmayr, Mario Huemer |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
business.industry
Computer science Noise reduction 020206 networking & telecommunications 010103 numerical & computational mathematics 02 engineering and technology Filter (signal processing) 01 natural sciences Adaptive filter Least mean squares filter 0202 electrical engineering electronic engineering information engineering Overhead (computing) Hardware_ARITHMETICANDLOGICSTRUCTURES 0101 mathematics Electrical and Electronic Engineering Performance improvement Projection (set theory) business Algorithm Digital signal processing |
| Zdroj: | IEEE Transactions on Circuits and Systems II: Express Briefs. 67:3507-3511 |
| ISSN: | 1558-3791 1549-7747 |
| Popis: | The least mean squares (LMS) filter is one of the most important adaptive filters used in digital signal processing applications. We present a performance improvement method for LMS filters based on null space projection. The approach uses buffering and a subsequent null space projection denoising. Interestingly, while the performance of this approach scales with the buffer length, the complexity in terms of multiplications per sample does not. We show the performance gains obtained by this method and present an architecture implementing an LMS filter as well as the proposed null space projection enhancement. We give complexity comparisons as well as synthesis results for a field-programmable gate array (FPGA) showing the low complexity overhead of the proposed method. We furthermore present hardware validated bit-true simulation results demonstrating the performance capabilities of the approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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