Publications-Detail
A Flexible Framework for Expectation Maximization-Based MIMO System Identification for Time-Variant Linear Acoustic Systems
- Authors:
- Kabzinski, T. , Jax, P.
- Journal:
- IEEE Open Journal of Signal Processing
- Volume:
- 5
- Page(s):
- 112--121
- number:
- Date:
- Nov. 2023
- ISSN:
- 2644-1322
- DOI:
- 10.1109/OJSP.2023.3337721
- Language:
- English
Abstract
Quasi-continuous system identification of time-variant linear acoustic systems can be applied in various audio signal processing applications when numerous acoustic transfer functions must be measured. A prominent application is measuring head-related transfer functions. We treat the underlying multiple-input-multiple-output (MIMO) system identification problem in a state-space model as a joint estimation problem for states, representing impulse responses, and state-space model parameters using the expectation maximization (EM) algorithm. We address limitations of prior work by imposing different model structures, especially for dependencies within a (transformed) state vector. This results in block diagonal matrix structures, for which we derive M-step update rules. Making assumptions about this model structure and choosing a block size for a given application define the computational complexity. In examples, we found that applying this framework yields improvements of up to 10dB in relative system distance in comparison to a conventional method.Download
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