两个神经元CNN用于假设检验

2012 13th International Workshop on Cellular Nanoscale Networks and their Applications Pub Date : 2012-10-18 DOI:10.1109/CNNA.2012.6331424

M. Vinyoles-Serra, X. Vilasís-Cardona

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引用次数: 1

摘要

在经典的假设检验问题中，采用双神经元连续时间细胞神经网络来定义统计量。该建议是基于线性费雪判别式的推广。描述了细胞神经网络参数的设置过程，并通过两个高斯分布假设的例子说明了其性能。这种技术也可以应用于概率分类问题或模式识别。

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Two neuron CNN for hypothesis testing

The two neuron continues time cellular neural network is used to define a statistic in the classical hypothesis testing problem. The proposal is based on a generalisation of the linear Fisher discriminant. The procedure to set the cellular neural network parameters is described and the performance shown on two examples with gaussianly distributed hypothesis. This technique might also be applied to probabilistic classification problems or pattern recognition.

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2012 13th International Workshop on Cellular Nanoscale Networks and their Applications

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