VkFFT is an efficient GPU-accelerated multidimensional Fast Fourier Transform library for Vulkan/CUDA/HIP/OpenCL/Level Zero/Metal projects. VkFFT aims to provide the ...
Researchers from the University of Cambridge and GlitterinTech, a startup founded by the same research group, have unveiled a fundamentally new type of optical spectrometer that delivers ...
Abstract: We present a novel form of Fourier analysis, and associated signal processing concepts, for signals (or data) indexed by edge-weighted directed acyclic graphs (DAGs). This means that our ...
Abstract: In image deconvolution problems, the diagonalization of the underlying operators by means of the fast Fourier transform (FFT) usually yields very large speedups. When there are incomplete ...
A differentiable fractional Fourier transform (FRFT) implementation with layers that can be trained end-to-end with the rest of the network. This package provides implementations of both fast ...
A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...
In part 3 of this series, we used the inverse fast Fourier transform (IFFT) to create 100-Hz time-domain waveforms of various amplitudes and phases. We can also use the IFFT to create waveforms ...
The Fourier transform (FT) is a fundamental technique for analysing signals that are generally dependent on time or space, although any other parameters are possible. It transforms a signal from the ...
This comprehensive article dissects sparse interactions, parameter sharing, pooling, and their profound impact on model efficiency. Delve into convolution as a potent prior, explore variants of the ...
In my previous article From Baby to Teenage Kyber I've explained how Kyber encryption/decryption works. As it was stated there, the essence of the algorithm is multiplication of polynomials in the ...
Fourier filter-based physics- information convolutional recurrent network for 2D incompressible flow
Physics-informed convolutional recurrent network (PhyCRNet) can solve partial differential equations without labeled data by encoding physics constraints into the loss function. However, the ...
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