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    • 4. 发明申请
    • NEURAL NETWORK LEARNING AND COLLABORATION APPARATUS AND METHODS
    • 神经网络学习与协作设备与方法
    • US20140089232A1
    • 2014-03-27
    • US13830398
    • 2013-03-14
    • Brain Corporation
    • Marius BuibasEugene M. IzhikevichBotond SzatmaryVadim Polonichko
    • G06N3/08
    • G06N3/08G06N3/04G06N3/049G06N3/10
    • Apparatus and methods for learning and training in neural network-based devices. In one implementation, the devices each comprise multiple spiking neurons, configured to process sensory input. In one approach, alternate heterosynaptic plasticity mechanisms are used to enhance learning and field diversity within the devices. The selection of alternate plasticity rules is based on recent post-synaptic activity of neighboring neurons. Apparatus and methods for simplifying training of the devices are also disclosed, including a computer-based application. A data representation of the neural network may be imaged and transferred to another computational environment, effectively copying the brain. Techniques and architectures for achieve this training, storing, and distributing these data representations are also disclosed.
    • 基于神经网络的设备学习和训练的装置和方法。 在一个实施方式中,每个装置包括多个加标神经元,其配置成处理感觉输入。 在一种方法中,使用交替的异质突触可塑性机制来增强装置内的学习和场分集。 替代可塑性规则的选择是基于最近邻近神经元的突触后活动。 还公开了用于简化设备训练的装置和方法,包括基于计算机的应用。 神经网络的数据表示可以被成像并传送到另一个计算环境,有效地复制大脑。 还公开了用于实现这种训练,存储和分发这些数据表示的技术和架构。