As applications, we also determine the forms of linear maps preserving group inverses.
作为应用又确定了保群逆线性映射形式。
The forms of linear maps preserving adjoint matrix between two full matrix rings have been given.
研究了全矩阵环上保持伴随矩阵的线性映射的形式。
Some striking examples of this are thegroupof invertible linear maps ormatrices, and theringof linear maps of a vector space.
一些引人注目的例子是集团的可逆线性映射或矩阵，和环的线性映射的向量空间。
This paper proposes one method of acquiring truly random bits by means of modulating the parameter of one-dimensional piecewise linear maps by arbitrarily distributed analogue random source.
提出了一种用任意分布的模拟随机源对一维分段线性映射的参数进行调制来获得真随机比特的方法。
Then, a theorem of the alternative for generalized subconvexlike set valued maps in real linear spaces is established.
然后，在实线性空间中建立了一个广义次似凸集值映射的择一性定理。
The role of hidden layer neurons of a RBF neural network can be interpreted as a function which maps input patterns from a nonlinear separable space to a linear separable space.
R BF神经网络的隐层神经元的作用可解释成从非线性可分空间向线性可分空间映射的函数。
The problem of the existence of a cone subdifferential for the cone convex set valued maps in the locally convex, linear and topological vector space is discussed.
在局部凸线性拓扑向量空间讨论了一种锥凸集值映射的锥次微分的存在性问题，证明了几个锥次微分的存在定理。
A state model map of piecewise linear resistive networks and its three fundamental operations are defined, and the operational rules of the maps are also given.
本文定义了分段线性电阻网络的状态模型图及其三种基本运算，给出了运算规律。
FNN efficiently maps the complex non-linear relationship between data by drill and rebound methods for its automatic learning, generation and fuzzy logic inference.
由于模糊神经网络具有很强的自学习、泛化和模糊逻辑推理功能，它可以有效地映射出钻芯、回弹数据间复杂的非线性关系。
FNN efficiently maps the complex non-linear relationship between data by drill and rebound methods for its automatic learning, generation and fuzzy logic inference.
由于模糊神经网络具有很强的自学习、泛化和模糊逻辑推理功能，它可以有效地映射出钻芯、回弹数据间复杂的非线性关系。
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