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Fast calculation of the Choi-Williams time-frequency distribution

机译:Choi-Williams时频分布的快速计算

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The method presented allows faster calculation of any time-frequency distribution with a kernel that can be formulated in the time-lag plane. Specific examples are the Wigner and Choi-Williams distributions. The Choi-Williams distribution (CWD) uses an exponential kernel in the generalized class of bilinear time-frequency distributions to achieve a reduction in the cross-term components of the distribution. Matrix manipulations provide an intuitive approach and, when combined with parallel processing, improve the processing speed to allow real-time calculations of the CWD. The use of an outer product matrix with a weighting matrix is particularly useful when evaluating different weighting parameters. For any given signal, the outer product matrix needs to be calculated just once. The various weighting matrices can be stored and used with any signal when needed. Parallel processing architectures allow implementation of the algorithm with speeds that are appropriate for real-time, running window calculations.
机译:提出的方法允许使用可以在时滞平面中制定的内核更快地计算任何时频分布。具体示例是Wigner和Choi-Williams分布。 Choi-Williams分布(CWD)在广义的双线性时频分布类中使用指数核,以实现分布的跨项分量的减少。矩阵操作提供了一种直观的方法,并且与并行处理结合使用时,可以提高处理速度,以实现CWD的实时计算。当评估不同的加权参数时,将外部乘积矩阵与加权矩阵一起使用特别有用。对于任何给定的信号,只需计算一次外部乘积矩阵。各种加权矩阵可以存储,并在需要时与任何信号一起使用。并行处理体系结构允许以适合实时运行窗口计算的速度实施算法。

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