Scalable neural hardware for the noisy-OR model of Bayesian networks
    5.
    发明授权
    Scalable neural hardware for the noisy-OR model of Bayesian networks 有权
    贝叶斯网络噪声或模型的可扩展神经硬件

    公开(公告)号:US09189729B2

    公开(公告)日:2015-11-17

    申请号:US13562187

    申请日:2012-07-30

    摘要: Embodiments of the invention relate to a scalable neural hardware for the noisy-OR model of Bayesian networks. One embodiment comprises a neural core circuit including a pseudo-random number generator for generating random numbers. The neural core circuit further comprises a plurality of incoming electronic axons, a plurality of neural modules, and a plurality of electronic synapses interconnecting the axons to the neural modules. Each synapse interconnects an axon with a neural module. Each neural module receives incoming spikes from interconnected axons. Each neural module represents a noisy-OR gate. Each neural module spikes probabilistically based on at least one random number generated by the pseudo-random number generator unit.

    摘要翻译: 本发明的实施例涉及用于贝叶斯网络的噪声-OR模型的可伸缩神经硬件。 一个实施例包括神经核心电路,其包括用于产生随机数的伪随机数发生器。 神经核心电路还包括多个输入电子轴突,多个神经模块以及将轴突与神经模块互连的多个电子突触。 每个突触将轴突与神经模块相互连接。 每个神经模块从相互联系的轴突接收进入的尖峰。 每个神经模块表示噪声或门。 每个神经模块基于由伪随机数发生器单元生成的至少一个随机数来概率地尖峰。

    Providing transposable access to a synapse array using column aggregation
    6.
    发明授权
    Providing transposable access to a synapse array using column aggregation 有权
    使用列聚合提供对突触阵列的可转位访问

    公开(公告)号:US08918351B2

    公开(公告)日:2014-12-23

    申请号:US13562203

    申请日:2012-07-30

    IPC分类号: G06N3/02 G06F15/18

    CPC分类号: G06N3/02 G06F15/18 G06N3/063

    摘要: Embodiments of the invention relate to providing transposable access to a synapse array using column aggregation. One embodiment comprises a neural network including a plurality of electronic axons, a plurality of electronic neurons, and a crossbar for interconnecting the axons with the neurons. The crossbar comprises a plurality of electronic synapses. Each synapse interconnects an axon with a neuron. The neural network further comprises a column aggregation module for transposable access to one or more synapses of the crossbar using column aggregation.

    摘要翻译: 本发明的实施方案涉及使用柱聚集来提供对突触阵列的可转位访问。 一个实施例包括包括多个电子轴突,多个电子神经元和用于将轴突与神经元互连的交叉开关的神经网络。 横杆包括多个电子突触。 每个突触将轴突与神经元相互连接。 所述神经网络还包括列聚集模块,用于使用柱聚集来转位地访问所述交叉开关的一个或多个突触。

    PROVIDING TRANSPOSABLE ACCESS TO A SYNAPSE ARRAY USING COLUMN AGGREGATION
    7.
    发明申请
    PROVIDING TRANSPOSABLE ACCESS TO A SYNAPSE ARRAY USING COLUMN AGGREGATION 有权
    使用柱聚合提供可扩展的访问到一个SYNPSE阵列

    公开(公告)号:US20140344201A1

    公开(公告)日:2014-11-20

    申请号:US13562203

    申请日:2012-07-30

    IPC分类号: G06N3/04 G06N3/08

    CPC分类号: G06N3/02 G06F15/18 G06N3/063

    摘要: Embodiments of the invention relate to providing transposable access to a synapse array using column aggregation. One embodiment comprises a neural network including a plurality of electronic axons, a plurality of electronic neurons, and a crossbar for interconnecting the axons with the neurons. The crossbar comprises a plurality of electronic synapses. Each synapse interconnects an axon with a neuron. The neural network further comprises a column aggregation module for transposable access to one or more synapses of the crossbar using column aggregation.

    摘要翻译: 本发明的实施方案涉及使用柱聚集来提供对突触阵列的可转位访问。 一个实施例包括包括多个电子轴突,多个电子神经元和用于将轴突与神经元互连的交叉开关的神经网络。 横杆包括多个电子突触。 每个突触将轴突与神经元相互连接。 所述神经网络还包括列聚集模块,用于使用柱聚集来转位地访问所述交叉开关的一个或多个突触。

    LOW-POWER EVENT-DRIVEN NEURAL COMPUTING ARCHITECTURE IN NEURAL NETWORKS
    8.
    发明申请
    LOW-POWER EVENT-DRIVEN NEURAL COMPUTING ARCHITECTURE IN NEURAL NETWORKS 有权
    神经网络中的低功率事件驱动神经计算体系结构

    公开(公告)号:US20140114893A1

    公开(公告)日:2014-04-24

    申请号:US13149754

    申请日:2011-05-31

    IPC分类号: G06N3/08

    摘要: A neural network includes an electronic synapse array of multiple digital synapses interconnecting a plurality of digital electronic neurons. Each synapse interconnects an axon of a pre-synaptic neuron with a dendrite of a post-synaptic neuron. Each neuron integrates input spikes and generates a spike event in response to the integrated input spikes exceeding a threshold. A decoder receives spike events sequentially and transmits the spike events to selected axons in the synapse array. An encoder transmits spike events corresponding to spiking neurons. A controller coordinates events from the synapse array to the neurons, and signals when neurons may compute their spike events within each time step, ensuring one-to-one correspondence with an equivalent software model. The synapse array includes an interconnecting crossbar that sequentially receives spike events from axons, wherein one axon at a time drives the crossbar, and the crossbar transmits synaptic events in parallel to multiple neurons.

    摘要翻译: 神经网络包括互连多个数字电子神经元的多个数字突触的电子突触阵列。 每个突触将突触前神经元的轴突与突触后神经元的枝晶相互连接。 每个神经元集成了输入尖峰,并响应于超过阈值的积分输入尖峰而产生尖峰事件。 解码器顺序地接收尖峰事件并将突发事件发送到突触阵列中的选定轴突。 编码器发送对应于尖峰神经元的尖峰事件。 控制器协调从突触阵列到神经元的事件,并且当神经元可以在每个时间步长内计算它们的尖峰事件时,发出信号,确保与等效的软件模型一一对应。 突触阵列包括从轴突顺序地接收尖峰事件的互连交叉开关,其中一次轴突一次驱动交叉开关,并且交叉开关将突触事件平行地传送到多个神经元。

    Providing transposable access to a synapse array using a recursive array layout
    9.
    发明授权
    Providing transposable access to a synapse array using a recursive array layout 有权
    使用递归数组布局提供对突触阵列的转座访问

    公开(公告)号:US09218564B2

    公开(公告)日:2015-12-22

    申请号:US13562195

    申请日:2012-07-30

    IPC分类号: G06N3/02 G06N3/04 G06N3/08

    摘要: Embodiments of the invention relate to providing transposable access to a synapse array using a recursive array layout. One embodiment comprises maintaining synaptic weights for multiple synapses connecting multiple axons and multiple neurons, wherein the synaptic weights are maintained based on a recursive array layout. The recursive array layout facilitates transposable access to the synaptic weights. A neuronal spike event between an axon and a neuron is communicated via a corresponding connecting synapse by accessing the synaptic weight of the corresponding connecting synapse in the recursive array layout.

    摘要翻译: 本发明的实施例涉及使用递归阵列布局提供对突触阵列的可转位访问。 一个实施例包括维持连接多个轴突和多个神经元的多个突触的突触权重,其中基于递归阵列布局维持突触权重。 递归数组布局有助于对突触权重的可转位访问。 通过访问递归阵列布局中相应连接突触的突触权重,通过相应的连接突触传达轴突和神经元之间的神经元尖峰事件。