使用FFTW.jl的多维时域卷积和互相关_Julia_下载.zip

### Operations This package aims for a fast implementation of the following operations: $$d_{i}=QF^{-1}[(F P g_i)(F P s_i)], \text{where}$$ * `s`: source signature in time * `g`: Green's functions in time * `d`: data in time * `F`: FFT operator * `P`: zero-padding matrix * `Q`: truncation matrix ### Usage ```julia nt=10; nr=10 g=randn(nt,nr); s=ones(nt, nr) ``` Create parameter variable and allocate memory. ``` pa=Conv.Param(dsize=[nt,nr], ssize=[nt,nr], gsize=[nt,nr], g=g, s=s) # memory allocation ``` And finally, perform a convolution. ``` Conv.mod!(pa, :d) #updates the data matrix in pa.d ``` [](https://travis-ci.org/pawbz/Conv.jl) [](https://codecov.io/gh/pawbz/Conv.jl)