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.
symiirorder1(input, c0, z1[, precision])	Implement a smoothing IIR filter with mirror-symmetric boundary conditions using a cascade of first-order sections. The second section uses a reversed sequence. This implements a system with the following transfer function and mirror-symmetric boundary conditions::.
symiirorder2(input, r, omega[, precision])	Implement a smoothing IIR filter with mirror-symmetric boundary conditions using a cascade of second-order sections. The second section uses a reversed sequence. This implements the following transfer function::.
lfilter(b, a, x[, axis, zi])	Filter data along one-dimension with an IIR or FIR filter.
lfiltic(b, a, y[, x])	Construct initial conditions for lfilter given input and output vectors.
lfilter_zi(b, a)	Construct initial conditions for lfilter for step response steady-state.
filtfilt(b, a, x[, axis, padtype, padlen, ...])	Apply a digital filter forward and backward to a signal.
savgol_filter(x, window_length, polyorder[, ...])	Apply a Savitzky-Golay filter to an array.
deconvolve(signal, divisor)	Deconvolves divisor out of signal using inverse filtering.
detrend(data[, axis, type, bp, overwrite_data])	Remove linear trend along axis from data.

Filter design

bilinear(b, a[, fs])	Return a digital IIR filter from an analog one using a bilinear transform.
bilinear_zpk(z, p, k, fs)	Return a digital IIR filter from an analog one using a bilinear transform.
savgol_coeffs(window_length, polyorder[, ...])	Compute the coefficients for a 1-D Savitzky-Golay FIR filter.