Consider two multi-dimensional digital signals, each with N s samples. For some number of lags N l N s , the cost of computing a single cross-correlation of these two signals is proportional to N s × N l . By exploiting several properties of Gaussian windows, we can compute N s local cross-correlations, again with computational cost proportional to N s ×N l . Here, local means the cross-correlation of signals after applying a Gaussian window centered on a single sample. Computational cost is independent of the size of the window.
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