【摘要】 在非线性多功能传感器的信号重构过程中,训练样本集不可避免地夹杂粗差数据。为了得到既有较强抗差性又有较高效率的估值,采用抗差最小二乘法在粗差干扰条件下进行参数估计。抗差最小二乘估计通过等价权把抗差估计原理与加权最小二乘形式结合在一起,因此在抵抗粗差的同时保持了最小二乘法的优点。非线性信号重构的粗差抑制结果表明,抗差最小二乘法计算速度快,且具有良好的抗粗差能力和收敛可靠性。更多还原

【Abstract】 Training sample set inevitably contains gross error in input signal reconstruction of nonlinear multifunctional sensor.In order to achieve the stronger robustness and the higher efficiency,Robust Least Squares(RLS)method is applied for parameter estimation under the disturbance of gross error.Based on the principle of equivalent weights,RLS method is combined with robust estimation theory and the Weighted Least Squares’ form,which can resist a certain degree of gross error and maintain the advantage of Least Squares regression method.As shown in the calculation results of gross error restraint in nonlinear signal reconstruction,the Robust Least Square method has favorable outlier resistance,convergence reliability and high calculating speed.更多还原