Performance Analysis and Coefficient Generation Method of Parallel Hammerstein Model Under Underdetermined Condition
Nanzhou Hu, Youyang Xiang, Mingyang Li, Xianglu Li, Jie Tian · 2025
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Description
Nanzhou Hu and co-authors analyze a nonlinear signal model used in radio gear in this 2025 paper. The parallel Hammerstein model mimics amplifiers with memory, but its mixed structure makes performance hard to predict and its settings hard to fit. The hard case is when data are too few to pin the settings down.
The team compares the model with a simpler polynomial rival using the same building blocks. A matrix factorization yields an exact formula for performance in the data-poor case. That formula ties performance to the rival model's strongest components. A new fitting method follows, choosing branches tied to those strong components. Simulations confirm near-best results with less complexity.
Catalog record
| CREATOR | Nanzhou Hu, Youyang Xiang, Mingyang Li, Xianglu Li, Jie Tian |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 46 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |