【摘要】 基于实时性、高精度的实际应用的要求,研究非线性函数的反函数的求法,提出验证反函数的精确度的标准,基于MATLAB 7.0的实验证明,需要建立反函数数值表,应用暖启动对牛顿迭代法扩展的算法来求是最优的;当精确度要求小于0.003时,应用BP神经网络算法是可行的;利用反函数的泰勒展开式得到反函数近似表达式,取三阶时精确度已小于0.003,完全可满足高精度要求同时实时性是最优的.更多还原

【Abstract】 This paper is based on the requirement of real time and high precision in practical application. The method of solving inverse function of nonlinear function is adopted and the standard for verifying the accuracy of inverse functions is put forward. Experimental proof based on MATLAB 7. 0. The results shows that an inverse function numerical table and the application of warm start to Newtonian iterative method are optimized. Secondly,it is feasible to apply BP neural network algorithm when the accuracy requirement is less than 0. 003. Finally,the inverse function approximation expression is obtained by the Taylor expansion of the inverse function and the accuracy of the third order is less than 0. 003,which can satisfy the high accuracy requirement and the real-time optimal performance.更多还原