Constrained deep learning is an advanced approach to training deep neural networks by incorporating domain-specific constraints into the learning process.

Abstract: Sparse linear arrays serve as the fundamental basis for sparse signal processing and have demonstrated remarkable direction-of-arrival (DOA) estimation performance. Due to the merit of ...

In this paper, the distributions of signal and ground TSVs in an array are optimized by conducting co-simulation of ANSYS Q2D and MATLAB based on genetic algorithm (GA). The optimization aims at ...

Wang, "Appendix C: IEEE30 Bus System Data," in Communication and Control in Electric Power Systems: Applications of Parallel and Distributed Processing, IEEE, 2003, pp. 493-495, doi: ...