天线阵列处理和电磁学的支持向量机

M. Martínez‐Ramón, C. Christodoulou
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引用次数: 84

摘要

支持向量机(SVM)作为分类和回归任务的一种新颖的非线性解决方案在90年代初被引入。由于其泛化能力和对噪声和干扰的鲁棒性,这些技术已被证明在各种实际应用中具有优异的性能。本书介绍了一套基于支持向量机的新技术,应用于天线阵列处理和电磁学。特别介绍了线性和非线性波束形成的方法以及阵列和电磁应用的参数设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Support Vector Machines for Antenna Array Processing and Electromagnetics
Support Vector Machines (SVM) were introduced in the early 90's as a novel nonlinear solution for classification and regression tasks. These techniques have been proved to have superior performances in a large variety of real world applications due to their generalization abilities and robustness against noise and interferences. This book introduces a set of novel techniques based on SVM that are applied to antenna array processing and electromagnetics. In particular, it introduces methods for linear and nonlinear beamforming and parameter design for arrays and electromagnetic applications.
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