The role of hidden layer neurons of a RBF neural network can be interpreted as a function which maps input patterns from a nonlinear separablespace to a linear separablespace.
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。
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Different from traditional parallel computations algorithms, Space-Time Adaptive Processing (STAP) algorithms are composed of several phases and each phase consists of many identical, separable tasks.