基于神经网络的噪声密度估计

Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop Pub Date : 1992-08-31 DOI:10.1109/NNSP.1992.253664

M. Musavi, D. Hummels, A. Laffely, S. Kennedy

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引用次数: 4

摘要

提出了一种用于估计未知噪声密度及其梯度的神经网络。网络结构类似于径向基函数。然而，学习规则是不同的，并且具有确保有效概率密度的无监督性质。该算法速度快，能很好地估计噪声密度。报道了一维和二维的例子。

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Noise density estimation using neural networks

A neural network for estimation of unknown noise densities and their gradients is presented. The network structure is similar to a radial basis function. The learning rule is, however, different and has an unsupervised nature that ensures a valid probability density. The algorithm is fast and provides good estimates of noise densities. One and two dimensional examples are reported.<>

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Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop

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