A low-latency rdp-cordic algorithm for real-time signal processing of edge computing devices in smart grid cyber-physical systems
M Qin, T Liu, B Hou, Y Gao, Y Yao, H Sun - Sensors, 2022 - mdpi.com
Smart grids are being expanded in scale with the increasing complexity of the equipment.
Edge computing is gradually replacing conventional cloud computing due to its low latency …
Edge computing is gradually replacing conventional cloud computing due to its low latency …
A Novel Fully Hardware-Implemented SVD Solver Based on Ultra-Parallel BCV Jacobi Algorithm
T Hu, X Li, X Yu, S Ren, L Yan, X Bai… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Efficient FPGA-based floating-point singular value decomposition (SVD) is challenging for its
enormous complexity with the rapid growth of the matrix dimension. Numerous hardware …
enormous complexity with the rapid growth of the matrix dimension. Numerous hardware …
Symbolic Regression Based Feature Extraction of Shallow Neural-Networks for Identification and Prediction
S Beyhan - Journal of Artificial Intelligence and Systems, 2022 - iecscience.org
This paper proposes a feature extraction method to improve the performance of shallow
neural-network models with less number of parameters to apply especially on embedded …
neural-network models with less number of parameters to apply especially on embedded …
A Task-Parallel and Reconfigurable FPGA-Based Hardware Implementation of Extreme Learning Machine
Extreme learning machine (ELM) is an emerging machine learning algorithm and widely
used in various real-world applications due to its extremely fast training speed, good …
used in various real-world applications due to its extremely fast training speed, good …