59 Understanding form and function in vascular tumours 54:28 A construction of Bowen-Margulis measure (Main talk) 55:52 A construction of Bowen-Margulis measure (Pre-Talk) 27:44 The question of q, a look at the interplay of number theory and ergodic theory i 57:37 The value distribution ...
Approximation on a domain X⊂R. A griding by 16 squares, numbered from 3 to 18, is used to associate each node with a hidden unit. The corresponding output connection sets the value of the function. For the sake of simplicity, in the figure, a 2D domain is gridded by uniform ...
在这个工作中,我们使用基于傅里叶的方法来研究基于梯度方法的一sinusoldal为激活函数的两层神经网络的基于梯度方法的泛化特性。我们证明了如果数据的分布具有很好的频域性质,如频带有限性,那么梯度方法就会收敛到具有泛化性的局部最小。我们还建立了基于傅里叶的在频带有限空间的泛化界,可以推广到其它激活函数。我们的泛...
Universal approximation property of ODENet and ResNet with a single activation function We study a universal approximation property of ODENet and ResNet. The ODENet is a map from an initial value to the final value of an ODE system in a finite... M Kimura,K Matsui,Y Mizuno 被引量: 0...
(NN); based on the values y (p) of a certain physical quantity y at several points x (p) =( x 1 (p) ,..., x n (p) ), the NN finds a dependence y = f(x 1 ,...,x n ) that explains all known observations and predicts the value of y for other x = (x1,...,xn)...
Here the emphasis is on the case of typical RBF networks, and the results show that a certain class of RBF networks with the same smoothing factor in each kernel node is broad enough for universal approximation. 展开 关键词: Theoretical or Mathematical/ function approximation neural nets/ radial...
that, under certain mild conditions on the kernel function (or activation function), the family of radial basis function neural networks obtained by replacing the usual translation with the Delsarte one, and taking the same smoothing factor in all kernel nodes, has the universal approximation ...
Universal approximationAbstract We prove that, under certain mild conditions on the kernel function (or activation function), the family of radial basis function neural networks obtained by replacing the usual translation with the Delsarte one, and taking the same smoothing factor in all kernel nodes...
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It is also an intricate part because the function value does not necessarily decrease monotonically in nonconvex acceleration methods. To overcome the non-monotonicity, previous analyses have employed different proof techniques. For example, Li and Lin [33] constructed a quadratic approximation of the...