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    • 2. 发明授权
    • Hierarchical temporal memory system with higher-order temporal pooling capability
    • 具有较高阶时间池能力的分层时间记忆系统
    • US08407166B2
    • 2013-03-26
    • US12483642
    • 2009-06-12
    • Jeffrey C. HawkinsDileep GeorgeCharles CurryFrank E. AstierAnosh RajRobert G. Jaros
    • Jeffrey C. HawkinsDileep GeorgeCharles CurryFrank E. AstierAnosh RajRobert G. Jaros
    • G06F15/18G06F17/10G06F17/16
    • G06N3/049
    • A temporal pooler for a Hierarchical Temporal Memory network is provided. The temporal pooler is capable of storing information about sequences of co-occurrences in a higher-order Markov chain by splitting a co-occurrence into a plurality of sub-occurrences. Each split sub-occurrence may be part of a distinct sequence of co-occurrences. The temporal pooler receives the probability of spatial co-occurrences in training patterns and tallies counts or frequency of transitions from one sub-occurrence to another sub-occurrence in a connectivity matrix. The connectivity matrix is then processed to generate temporal statistics data. The temporal statistics data is provided to an inference engine to perform inference or prediction on input patterns. By storing information related to a higher-order Markov model, the temporal statistics data more accurately reflects long temporal sequences of co-occurrences in the training patterns.
    • 提供了一种用于分层时域存储器网络的时间池。 时间池能够通过将共现分裂为多个次出现来存储关于高阶马尔可夫链中的共现序列的信息。 每个分裂子事件可以是共同出现的不同序列的一部分。 时间分组器接收训练模式中的空间共现概率,并且在连接矩阵中从一个子出现转换到另一个子出现的计数计数或转换频率。 然后处理连通性矩阵以生成时间统计数据。 将时间统计数据提供给推理机以对输入模式执行推断或预测。 通过存储与高阶马尔科夫模型相关的信息,时间统计数据更准确地反映训练模式中共同出现的长时间序列。
    • 4. 发明申请
    • HIERARCHICAL TEMPORAL MEMORY SYSTEM WITH HIGHER-ORDER TEMPORAL POOLING CAPABILITY
    • 具有较高时间平移能力的分层时间记忆系统
    • US20090313193A1
    • 2009-12-17
    • US12483642
    • 2009-06-12
    • Jeffrey C. HawkinsDileep GeorgeCharles CurryFrank E. AstierAnosh RajRobert G. Jaros
    • Jeffrey C. HawkinsDileep GeorgeCharles CurryFrank E. AstierAnosh RajRobert G. Jaros
    • G06F15/18G06N5/04G06N3/12
    • G06N3/049
    • A temporal pooler for a Hierarchical Temporal Memory network is provided. The temporal pooler is capable of storing information about sequences of co-occurrences in a higher-order Markov chain by splitting a co-occurrence into a plurality of sub-occurrences. Each split sub-occurrence may be part of a distinct sequence of co-occurrences. The temporal pooler receives the probability of spatial co-occurrences in training patterns and tallies counts or frequency of transitions from one sub-occurrence to another sub-occurrence in a connectivity matrix. The connectivity matrix is then processed to generate temporal statistics data. The temporal statistics data is provided to an inference engine to perform inference or prediction on input patterns. By storing information related to a higher-order Markov model, the temporal statistics data more accurately reflects long temporal sequences of co-occurrences in the training patterns.
    • 提供了一种用于分层时域存储器网络的时间池。 时间池能够通过将共现分裂为多个次出现来存储关于高阶马尔可夫链中的共现序列的信息。 每个分裂子事件可以是共同出现的不同序列的一部分。 时间分组器接收训练模式中的空间共现概率,并且在连接矩阵中从一个子出现转换到另一个子出现的计数计数或转换频率。 然后处理连通性矩阵以生成时间统计数据。 将时间统计数据提供给推理机以对输入模式执行推断或预测。 通过存储与高阶马尔科夫模型相关的信息,时间统计数据更准确地反映训练模式中共同出现的长时间序列。