Hunan Mijie Leading Education Technology Co., Ltd.: Python Core Library Upgrades Accelerate Data Science Development

Hunan Mijie Leading Education Technology Co., Ltd.: Python Core Library Upgrades Accelerate Data Science Development ...
IEEE

Sparse Array Wideband Beamforming Based on Covariance Matrix Reconstruction and Neural Network

Abstract: Sparse arrays offer economic advantages by reducing the number of antennas. However, directly utilizing the covariance matrix of sparse array signals for wideband beamforming may lead to the ...
Hosted on MSN

Python Physics; Rigid Body Rotations Using the Rotation Matrix and the Inverse Inertia Tensor

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...
GitHub

Converting user libraries of SciPy sparse matrix to sparse array

If folks have libraries who are using SciPy sparse matrices, and you'd like help converting them to run/work with sparse array, this sounds like a nice opportunity to work that out. I wrote a ...
GitHub

[Python] Compatibility with SciPy 1.15's stricter sparse code

The test suite in conda-forge/arrow-cpp-feedstock#1664 has a single test failure ===== FAILURES ===== _____ test_sparse_coo_tensor_scipy_roundtrip[f2-arrow_type8 ...
Semiconductor Engineering

Distributed Radar Signal Processing Utilizing A Sparse Array To Obfuscate The Data

A new technical paper titled “Signal processing architecture for a trustworthy 77GHz MIMO Radar” was published by researchers at Fraunhofer FHR, Ruhr University Bochum, and Wavesense Dresden GmbH.
Frontiers

A TMSBL underwater acoustic channel estimation method based on dictionary learning denoising

1 School of Electrical and Information Technology, Yunnan Minzu University, Kunming, China 2 Yunnan Key Laboratory of Unmanned Autonomous System, Yunnan Minzu University, Kunming, China The shallow ...
IEEE

A Balanced Sparse Matrix Convolution Accelerator for Efficient CNN Training

Abstract: Sparse Convolutional Neural Network (CNN) training is well known to be time-consuming due to significant off-chip memory traffic. To effectively deploy sparse training, existing accelerators ...