Signal

Ant Colony Optimization (ACO) is an optimization metaheuristic based on the foraging behavior of ants. This metaheuristic was originally proposed to find good solutions to discrete combinatorial problems. Many extensions of the ACO heuristic for continuous domain have been proposed, but even those that claim close similarity with classical (discrete domain) ACO, like ACOR, do not use the heuristic information called visibility, commonly used in the original ACO algorithm. In this paper, we show the importance of the visibility in ACO, by proposing ACOℝ -V , a variant of ACOR that performs better in a number of benchmark functions.

it is related to bug algorithm in motion planning

复杂网络中寻找特定边，删除边和增加边的源程序(A source program for finding specific edges, deleting edges, and increasing edges in complex networks)

案例算法，基于数量损失和品质衰减的生鲜农产品供应链协调。(Case algorithm, based on the number of losses and quality attenuation fresh agricultural products supply chain coordination.)

谱减法语音增强。第一行为文件读取，需自行修改输入的语音。(Spectral subtraction speech enhancement. The first line reads the file, need to modify the input voice.)

power system stability equal area matlab code

说明：  用分布傅立叶法求解薛定谔方程的matlab程序(Schrodinger equation matlab program)

电能质量数据压缩，基于小波变换的（如Db3 haar）压缩(Power quality data compression, wavelet transform (such as Db3 haar) compression)

Objective Fidelity Criteria(Objective Criteria)

接收端自适应均衡器的LMS算法MATLAB仿真实现(Receiver adaptive equalizer of LMS algorithm MATLAB simulation)