公开(公告)号：EP1949313A1

公开(公告)日：2008-07-30

申请号：EP06804525.1

申请日：2006-11-15

申请人： Garner, Bernadette

发明人： Garner, Bernadette

IPC分类号： G06N3/08

CPC分类号： G06N3/082 ,  G06N3/0481 ,  G06N3/088

摘要： The present invention provides a method (30) for training an artificial neural network (NN). The method (30) includes the steps of: initialising the NN by selecting an output of the NN to be trained and connecting an output neuron of the NN to input neuron(s) in an input layer of the NN for the selected output; preparing a data set to be learnt by the NN; and, applying the prepared data set to the NN to be learnt by applying an input vector of the prepared data set to the first hidden layer of the NN, or the output layer of the NN if the NN has no hidden layer(s), and determining whether at least one neuron for the selected output in each layer of the NN can learn to produce the associated output for the input vector. If none of the neurons in a layer of the NN can learn to produce the associated output for the input vector, then a new neuron is added to that layer to learn the associated output which could not be learnt by any other neuron in that layer. The new neuron has its output connected to all neurons in next layer that are relevant to the output being trained. If an output neuron cannot learn the input vector, then another neuron is added to the same layer as the current output neuron and all inputs are connected directly to it. This neuron learns the input the old output could not learn. An additional neuron is added to the next layer. The inputs to this neuron are the old output of the NN, and the newly added neuron to that layer.

公开(公告)号：EP2533176A1

公开(公告)日：2012-12-12

申请号：EP12183557.3

申请日：2006-11-15

申请人： Garner, Bernadette

发明人： Garner, Bernadette

IPC分类号： G06N3/08

CPC分类号： G06N3/082 ,  G06N3/0481 ,  G06N3/088

摘要： The present invention provides a method for determining whether an input vector is known or unknown by a neuron. The method includes the steps of: constructing a constraint and its complement from the input vector; alternately adding the constraint and its complement to the constraints set of the neuron; and testing the constraints set to determine if there is a solution in either case. If there is a solution for either the constraint or its complement, but not both, it is determined that the input vector is known by the neuron, and if there is a solution when both the constraint and its complement are alternately added to the constraints set, it is determined that the input vector is not known by the neuron.

摘要翻译： 本发明提供了是否输入矢量是已知的或由神经元未知确定性采矿的方法。 该方法包括以下步骤：构造一约束，并从输入向量及其互补序列; 或者添加约束和补充设定神经元的限制; 如果有测试设置为确定性矿的约束在两种情况下的解决方案。 如果存在用于无论是约束或它的互补物，但不是两者的溶液中，它是确定性的开采并输入矢量是由神经元已知的，并且如果有一个解决方案时，这两个约束及其互补交替加入到设置的约束 时，确定性的开采并输入矢量不被神经元已知的。

公开(公告)号：EP1949313A4

公开(公告)日：2010-03-31

申请号：EP06804525

申请日：2006-11-15

申请人： GARNER BERNADETTE

发明人： GARNER BERNADETTE

IPC分类号： G06N3/08

CPC分类号： G06N3/082 ,  G06N3/0481 ,  G06N3/088