Neural Networks Based Modeling with Adaptive Selection of Hidden Layer's Node for Path Loss Model
- Authors
- 강창호; 조성윤
- Issue Date
- 2019
- Publisher
- 사단법인 항법시스템학회
- Keywords
- auto-encoder network; adaptive selection of hidden layer' s node; LTE path loss model; signal strength attenuation
- Citation
- Journal of Positioning, Navigation, and Timing, v.8, no.4, pp.193 - 200
- Journal Title
- Journal of Positioning, Navigation, and Timing
- Volume
- 8
- Number
- 4
- Start Page
- 193
- End Page
- 200
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/17285
- DOI
- 10.11003/JPNT.2019.8.4.193
- ISSN
- 2288-8187
- Abstract
- The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.
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Collections - School of Mechanical System Engineering > 1. Journal Articles
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