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Systems and methods for converting discrete wavelets to tensor fields and using neural networks to process tensor fields

机译:将离散小波转换为张力字段的系统和方法,并使用神经网络处理张力字段

摘要

The present disclosure relates to systems and methods for detecting and identifying anomalies within a discrete wavelet database. In one implementation, the system may include one or more memories storing instructions and one or more processors configured to execute the instructions. The instructions may include instructions to receive a new wavelet, convert the net transaction to a wavelet, convert the wavelet to a tensor using an exponential smoothing average, calculate a difference field between the tensor and a field having one or more previous transactions represented as tensors, perform a weighted summation of the difference field to produce a difference vector, apply one or more models to the difference vector to determine a likelihood of the new wavelet representing an anomaly, and add the new wavelet to the field when the likelihood is below a threshold.
机译:本公开涉及用于检测和识别离散小波数据库内的异常的系统和方法。在一个实现中,系统可以包括存储指令的一个或多个存储器和配置为执行指令的一个或多个处理器。指令可以包括接收新小波的指令,将网络事务转换为小波,使用指数平滑平均将小波转换为张量,计算张量和具有表示为张量的一个或多个以前交易的字段之间的差值,执行差异字段的加权求和以产生差异矢量,将一个或多个模型应用于差异矢量,以确定表示异常的新小波的可能性,并在可能性下方时将新小波添加到该字段中临界点。

著录项

  • 公开/公告号US11036824B2

    专利类型

  • 公开/公告日2021-06-15

    原文格式PDF

  • 申请/专利权人 DEEP LABS INC.;

    申请/专利号US202017014428

  • 发明设计人 PATRICK FAITH;

    申请日2020-09-08

  • 分类号G06F17/14;G06N3/08;G06N3/04;G06N3/02;

  • 国家 US

  • 入库时间 2022-08-24 19:19:35

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