Belief Propagation With Optimized Pool Size for Non-Adaptive Group Testing: An Empirical Study
In this paper, an empirical study shows that positive tests containing multiple defectives are unlikely to provide effective messages in belief propagation (BP) for non-adaptive group testing. Thus, an objective function is proposed to measure the effectiveness of messages over edges, especially in...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9913428/ |
| Summary: | In this paper, an empirical study shows that positive tests containing multiple defectives are unlikely to provide effective messages in belief propagation (BP) for non-adaptive group testing. Thus, an objective function is proposed to measure the effectiveness of messages over edges, especially in the low-noise region. The maximization of the objective function allows us to optimize the pool size for BP. Simulation results show that the error performance of BP in the low-noise region is significantly improved by our pool size optimization. |
|---|---|
| ISSN: | 2169-3536 |