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SYSTEM AND METHOD FOR SIGNAL PRE-PROCESSING BASED ON DATA DRIVEN MODELS AND DATA DEPENDENT MODEL TRANSFORMATION

机译:基于数据驱动模型和数据相关模型变换的信号预处理系统和方法

摘要

This disclosure relates generally to method for signal pre-processing based on a plurality of data driven models and a data dependent model transformation. The method includes (a) receiving, a raw signal as an input; (b) learning, a set of representational basis from the received raw signal, wherein the set of representational basis comprises a plurality of orthonormal vectors; (c) selecting, at least one orthonormal vector from the plurality of orthonormal vectors, (d) determining, a structure of the plurality of dictionary atoms, wherein structure of the plurality of dictionary atoms corresponds to a graph structure represented as a Laplacian matrix (L); (e) integrating, the graph structure as a structure of the set of representational basis to obtain a reconfigured data model; and (f) reconstructing, using the reconfigured data model to obtain a denoised signal, wherein at least one of constraints on a optimization problem corresponds to desired spectral and topological structure.
机译:本公开总体上涉及用于基于多个数据驱动的模型和数据相关的模型变换的信号预处理的方法。该方法包括:(a)接收原始信号作为输入; (b)从接收到的原始信号中学习一组代表基础,其中该组代表基础包括多个正交向量; (c)从多个正交向量中选择至少一个正交向量,(d)确定多个词典原子的结构,其中多个词典原子的结构对应于表示为拉普拉斯矩阵的图结构( L); (e)将图结构作为一组表示基础的结构进行集成,以获得重新配置的数据模型; (f)使用重新配置的数据模型重建以获得去噪的信号,其中,对优化问题的约束中的至少一个对应于期望的频谱和拓扑结构。

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