异型RFID天线神经空间映射建模研究进展

Shuxia Yan, Zhifeng Chen, Weiguang Shi, F. Feng
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引用次数: 0

摘要

随着技术的发展,射频(RF)天线增益估计方法需要克服建模过程复杂、建模周期长、模型精度低等问题。传统的建模方法已经不能满足现代器件建模的要求。本文介绍了一种将神经空间映射(neurosm)模型与粒子群优化算法相结合的估计框架。仿真结果表明,该方法可以提高现有模型的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review of Neuro-Space Mapping Modeling for Heteromorphic RFID Antennas
With the development of technology, the radio frequence (RF) antenna gain estimation methods need to overcome some problems, such as complex modeling processes, long modeling cycles, and low model accuracy. The traditional methods are unable to meet modern device modeling requirements. This paper introduces an estimation framework, which combine neuro-space mapping (Neuro-SM) model with the particle swarm optimiser algorithm. Simulation results show that this method can improve the accuracy of existing models.
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