Dept. of Comput. Sci. Eng., Sathyabama Univ., Chennai, India;
approximation theory; interpolation; multilayer perceptrons; probability; AI; ANN; PMC; affine functional; approximation properties; arbitrary decision regions; artificial neural networks; continuous feedforward neural networks; continuous function; continuous sigmoidal nonlinearity; electric power consumption; entrance variables; exit variables; finite linear combinations; fixed-univariate function; interpolation algorithms; mild conditions; multiperceptron layer; probabilistic neural networks; real variables; sigmoid;
机译:利用人工神经网络建模的非拟隐蔽层激活函数的通用逼近
机译:具有任意激活函数的神经网络对非线性算子的通用逼近及其在动力学系统中的应用
机译:多层规则模糊神经网络对连续模糊值函数的通用逼近
机译:普遍逼近使用SigMoid激活功能的概率神经网络
机译:反向传播神经网络中新的Sigmoid函数的实现。
机译:使用正算时深层神经网络中激活函数的快速逼近
机译:多层神经网络在乙型肝炎病毒诊断中的应用 - 近似于乙状结肠激活功能
机译:神经网络对p均值的通用逼近