公开(公告)号：US20090287624A1

公开(公告)日：2009-11-19

申请号：US12158134

申请日：2006-12-22

Applicant: Jean Rouat ,  Ramin Pichevar ,  Stephane Loiselle ,  Le Tan Thanh Tai ,  Anh Hoang Hai ,  Jean Lavoie ,  Jocelyn Bergeron

Inventor： Jean Rouat ,  Ramin Pichevar ,  Stephane Loiselle ,  Le Tan Thanh Tai ,  Anh Hoang Hai ,  Jean Lavoie ,  Jocelyn Bergeron

IPC: G06G7/00 ,  G06F15/18 ,  G06K9/00 ,  G06N3/02

CPC classification number: G06N3/049 ,  G06K9/4623 ,  G06K9/6212

Abstract: A system and method for characterizing a pattern, in which a spiking neural network having at least one layer of neurons is provided. The spiking neural network has a plurality of connected neurons for transmitting signals between the connected neurons. A model for inducing spiking in the neurons is specified. Each neuron is connected to a global regulating unit for transmitting signals between the neuron and the global regulating unit. Each neuron is connected to at least one other neuron for transmitting signals from this neuron to the at least one other neuron, this neuron and the at least one other neuron being on the same layer. Spiking of each neuron is synchronized according to a number of active neurons connected to the neuron. At least one pattern is submitted to the spiking neural network for generating sequences of spikes in the spiking neural network, the sequences of spikes (i) being modulated over time by the synchronization of the spiking and (ii) being regulated by the global regulating unit. The at least one pattern is characterized according to the sequences of spikes generated in the spiking neural network.

Abstract translation: 一种用于表征图案的系统和方法，其中提供具有至少一层神经元的尖峰神经网络。 刺激神经网络具有用于在连接的神经元之间传输信号的多个连接的神经元。 规定了在神经元中诱发尖峰的模型。 每个神经元连接到全局调节单元，用于在神经元和全局调节单元之间传输信号。 每个神经元连接到至少一个其他神经元，用于将信号从该神经元发送到至少一个其他神经元，该神经元和至少一个其他神经元位于相同的层上。 根据连接到神经元的多个活跃神经元，每个神经元的尖峰被同步。 至少一种模式被提交到加标神经网络，用于在加标神经网络中产生尖峰序列，尖峰序列（i）随着时间的推移而被调频，并且（ii）由全局调节单元 。 至少一个图案根据在加标神经网络中产生的尖峰的序列来表征。

公开(公告)号：US08346692B2

公开(公告)日：2013-01-01

申请号：US12158134

申请日：2006-12-22

Applicant: Jean Rouat ,  Ramin Pichevar ,  Stephane Loiselle ,  Le Tan Thanh Tai ,  Anh Hoang Hai ,  Jean Lavoie ,  Jocelyn Bergeron

Inventor： Jean Rouat ,  Ramin Pichevar ,  Stephane Loiselle ,  Le Tan Thanh Tai ,  Anh Hoang Hai ,  Jean Lavoie ,  Jocelyn Bergeron

IPC: G06G7/00

CPC classification number: G06N3/049 ,  G06K9/4623 ,  G06K9/6212

Abstract: A spiking neural network has a layer of connected neurons exchanging signals. Each neuron is connected to at least one other neuron. A neuron is active if it spikes at least once during a time interval. Time-varying synaptic weights are computed between each neuron and at least one other neuron connected thereto. These weights are computed according to a number of active neurons that are connected to the neuron. The weights are also computed according to an activity of the spiking neural network during the time interval. Spiking of each neuron is synchronized according to a number of active neurons connected to the neuron and according to the weights. A pattern is submitted to the spiking neural network for generating sequences of spikes, which are modulated over time by the spiking synchronization. The pattern is characterized according to the sequences of spikes generated in the spiking neural network.

Abstract translation: 刺激神经网络具有交换信号的连接神经元层。 每个神经元连接到至少一个其他神经元。 如果一个神经元在一段时间间隔内至少闪一次，则它是活跃的。 在每个神经元和与其连接的至少一个其他神经元之间计算时变突触权重。 这些权重根据连接到神经元的多个活动神经元来计算。 还可以根据时间间隔内刺激神经网络的活动来计算权重。 每个神经元的尖峰根据连接到神经元的多个活动神经元并根据权重进行同步。 一个模式被提交到加标神经网络，用于产生尖峰序列，随着时间的推移，尖峰同步被调制。 根据尖峰神经网络中产生的尖峰序列，对该图案进行表征。