Beyond its methodological contribution, the study offers new insights into how stimulus-driven variability and internally generated gain fluctuations evolve over time and between brain areas. The ...

Abstract: In recent years, numerous recurrent neural network (RNN) models have been reported for solving time-dependent nonlinear optimization problems. However, few existing RNN models simultaneously ...

Abstract: Utilizing various auxiliary optimization problems (AOPs) to help the optimization for constrained multiobjective problems (CMOPs) has recently drawn substantial attention. However, two key ...

Globally, subtle hydrocarbon reservoirs in petroliferous basins have always been challenging targets for exploration research, with thin sand body reservoir prediction being a key focus in this field.

This is the MATLAB code for the implementation of neural pupil engineering FPM (NePE-FPM), an optimization framework for FPM reconstruction for off-axis areas. NePE-FPM engineers the pupil function ...

cuADMM solves multi-block SDP problems of the form: $$\min_X \left\langle C,X\right\rangle \quad\text{s.t.}\quad \begin{cases} \left\langle A_i,X\right\rangle = b_i ...