A structured review of sparse fast Fourier transform algorithms
E Rajaby, SM Sayedi - Digital Signal Processing, 2022 - Elsevier
Discrete Fourier transform (DFT) implementation requires high computational resources and
time; a computational complexity of order O (N 2) for a signal of size N. Fast Fourier …
time; a computational complexity of order O (N 2) for a signal of size N. Fast Fourier …
Recent developments in the sparse Fourier transform: A compressed Fourier transform for big data
The discrete Fourier transform (DFT) is a fundamental component of numerous
computational techniques in signal processing and scientific computing. The most popular …
computational techniques in signal processing and scientific computing. The most popular …
A bandwidth efficient dual-function radar communication system based on a MIMO radar using OFDM waveforms
Z Xu, A Petropulu - IEEE Transactions on Signal Processing, 2023 - ieeexplore.ieee.org
A novel dual-function radar communication (DFRC) system is proposed, that achieves high
communication rate, and can flexibly trade-off rate for improved sensing performance. The …
communication rate, and can flexibly trade-off rate for improved sensing performance. The …
Light field reconstruction using sparsity in the continuous fourier domain
Sparsity in the Fourier domain is an important property that enables the dense
reconstruction of signals, such as 4D light fields, from a small set of samples. The sparsity of …
reconstruction of signals, such as 4D light fields, from a small set of samples. The sparsity of …
GHz-wide sensing and decoding using the sparse Fourier transform
We present BigBand, a technology that can capture GHz of spectrum in realtime without
sampling the signal at GS/s-ie, without high speed ADCs. Further, it is simple and can be …
sampling the signal at GS/s-ie, without high speed ADCs. Further, it is simple and can be …
Linear-depth quantum circuits for loading Fourier approximations of arbitrary functions
The ability to efficiently load functions on quantum computers with high fidelity is essential
for many quantum algorithms, including those for solving partial differential equations and …
for many quantum algorithms, including those for solving partial differential equations and …
An overview of advances in signal processing techniques for classical and quantum wideband synthetic apertures
P Vouras, KV Mishra, A Artusio-Glimpse… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Rapid developments in synthetic aperture (SA) systems, which generate a larger aperture
with greater angular resolution than is inherently possible from the physical dimensions of a …
with greater angular resolution than is inherently possible from the physical dimensions of a …
A fast face detection method via convolutional neural network
Current face or object detection methods via convolutional neural network (such as
OverFeat, R-CNN and DenseNet) explicitly extract multi-scale features based on an image …
OverFeat, R-CNN and DenseNet) explicitly extract multi-scale features based on an image …
50 years of FFT algorithms and applications
The fast Fourier transform (FFT) algorithm was developed by Cooley and Tukey in 1965. It
could reduce the computational complexity of discrete Fourier transform significantly from O …
could reduce the computational complexity of discrete Fourier transform significantly from O …
[HTML][HTML] Efficient MPS representations and quantum circuits from the Fourier modes of classical image data
B Jobst, K Shen, CA Riofrío, E Shishenina… - Quantum, 2024 - quantum-journal.org
Abstract Machine learning tasks are an exciting application for quantum computers, as it has
been proven that they can learn certain problems more efficiently than classical ones …
been proven that they can learn certain problems more efficiently than classical ones …