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Estimating Parameterized Scalable Models From the Best Linear Approximation of Nonlinear Systems for Accurate High-Level Simulations

机译:从非线性系统的最佳线性逼近估计参数化可伸缩模型,以进行精确的高级仿真

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摘要

System designers of communication systems need to compare the simulated behavior of a system with the linear and nonlinear specifications. They need high-level models to perform these simulations fast. The existing high-level models for nonlinear components do not scale smoothly with external parameters like the input power. To overcome this problem, a modeling technique based on the best linear approximation is developed. The parameterized models describe trajectories of the poles and zeros as a function of the input power. The resulting models accurately describe both the linear and nonlinear behavior of the system components. They can easily be implemented in modern simulators.
机译:通信系统的系统设计人员需要将系统的仿真行为与线性和非线性规范进行比较。他们需要高级模型来快速执行这些仿真。现有的非线性组件高级模型无法随着外部参数(例如输入功率)平滑缩放。为了克服这个问题,开发了基于最佳线性逼近的建模技术。参数化模型将极点和零点的轨迹描述为输入功率的函数。生成的模型准确地描述了系统组件的线性和非线性行为。它们可以在现代模拟器中轻松实现。

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