Signal processing (cupyx.scipy.signal)

Hint

SciPy API Reference: Signal processing (scipy.signal)

Convolution

convolve(in1, in2[, mode, method])

Convolve two N-dimensional arrays.

correlate(in1, in2[, mode, method])

Cross-correlate two N-dimensional arrays.

fftconvolve(in1, in2[, mode, axes])

Convolve two N-dimensional arrays using FFT.

oaconvolve(in1, in2[, mode, axes])

Convolve two N-dimensional arrays using the overlap-add method.

convolve2d(in1, in2[, mode, boundary, fillvalue])

Convolve two 2-dimensional arrays.

correlate2d(in1, in2[, mode, boundary, …])

Cross-correlate two 2-dimensional arrays.

sepfir2d(input, hrow, hcol)

Convolve with a 2-D separable FIR filter.

choose_conv_method(in1, in2[, mode])

Find the fastest convolution/correlation method.

Filtering

order_filter(a, domain, rank)

Perform an order filter on an N-D array.

medfilt(volume[, kernel_size])

Perform a median filter on an N-dimensional array.

medfilt2d(input[, kernel_size])

Median filter a 2-dimensional array.

wiener(im[, mysize, noise])

Perform a Wiener filter on an N-dimensional array.
cupyx.scipy.ndimage.white_tophat cupyx.scipy.signal.convolve