The problem of parameter estimation from a standard vector linear regression equation in the absence of sufficient excitation in the regressor is addressed. The first step to solve the problem consists in transforming this equation into a set of scalar ones using the well-known dynamic regressor extension and mixing technique. Then a novel procedure to generate new scalar exciting regressors is proposed.} The superior performance of a classical gradient estimator using this new regressor, instead of the original one, is illustrated with comprehensive simulations.

翻译：在递减器没有足够刺激的情况下,标准矢量线性回归方程式的参数估计问题得到了解决。解决问题的第一步是使用众所周知的动态递减器延伸和混合技术将这个方程式转换成一套螺旋弧。然后提出了产生新的斜弧振动递减器的新程序。}使用这个新的递减器而不是原来的递减器的古典梯度估计器的优异性能用全面模拟来说明。