For the large sparse generalized absolute value equations (GAVEs) , the shift splitting for the linear part's coefficient matrix is utilized to establish a new modified Newton-type (NMN) iteration method. The conditions for the convergence of the NMN iteration method are discussed in depth. Furthermore, certain sufficient convergence conditions are obtained when the coefficient matrix is a symmetric positive definite matrix or an $H_{+}$-matrix. According to both two numerical examples, the NMN iteration method is an effective approach to solve the GAVEs, especially when the coefficient matrix is indefinite.

翻译：对于数量稀少的普遍绝对值方程式(GAVES),线性部分系数矩阵的转移分割被用来确定新的修改牛顿型(NMN)迭代法;深入讨论NMN迭代法趋同的条件;此外,当系数矩阵为对称正数确定矩阵或$H ⁇ $-$-matrix时,获得某些足够的趋同条件;根据两个数字示例,NMN迭代法是解决GAVes的有效办法,特别是当系数矩阵是无限期的时。