论文标题
足够的条件，可以通过步骤和relu激活功能进行激发的持久性
Sufficient Conditions for Persistency of Excitation with Step and ReLU Activation Functions
论文作者
论文摘要
本文定义了几何标准，然后使用这些标准来建立足够的条件，以持续使用具有阶跃或relu激活功能的单个隐藏层神经网络构建的向量函数。我们表明，在使用参考系统跟踪时，这些条件一直存在，就像自适应控制中所做的那样。我们在该类型的线性参数化激活的系统上以数值来证明结果，并证明参数估计值与满足足够的条件相关地收敛到真实值。
This paper defines geometric criteria which are then used to establish sufficient conditions for persistency of excitation with vector functions constructed from single hidden-layer neural networks with step or ReLU activation functions. We show that these conditions hold when employing reference system tracking, as is commonly done in adaptive control. We demonstrate the results numerically on a system with linearly parameterized activations of this type and show that the parameter estimates converge to the true values with the sufficient conditions met.
