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Takes a matrix of numeric values and smoothes it by convolution with a symmetric Gaussian window function.
gaussianSmooth2D(m, kernelSize = 5, kernelSD = 0.5, plotKernel = FALSE)
Returns a numeric matrix of the same dimensions as input.
input matrix (numeric, on any scale, doesn't have to be square)
the size of the Gaussian kernel, in points
the SD of the Gaussian kernel relative to its size (.5 = the edge is two SD's away)
if TRUE, plots the kernel
modulationSpectrum
s = spectrogram(soundgen(), samplingRate = 16000, output = 'original', plot = FALSE) # image(log(s)) s1 = gaussianSmooth2D(s, kernelSize = 11, plotKernel = TRUE) # image(log(s1))
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