JiDai

This file is about the working of modified sub oscillation method of generating PWM.

The backward-forward sweep algorithm is applied to a distribution system as part of it s load flow analysis. The states of the buses are therefore attained.

使用蟻群演算法來求解旅行推銷員問題於matlab上(Using ant colony algorithm to solve the traveling salesman problem in matlab)

DOA估计常用算法，包括：music算法，卡尔曼滤波算法，自适应梯度算法，空间平滑算法，改进的空间平滑算法。(DOA estimation algorithm used, including: music algorithm, Kalman filter algorithm, adaptive gradient algorithm, spatial smoothing algorithm, the improved spatial smoothing algorithm.)

kalman滤波程序，用matlab编的，可以参考(Kalman filtering procedures, using Matlab series, we can make reference to)

This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot navigation and others (see references for more info). Because of some architectural features of convolutional networks, such as weight sharing it is imposible to implement it using Matlab Neural Network Toolbox without it s source modifications.

三相异步电机启动，变压器启动matlab仿真，希望对大家有帮助(Three-phase induction motor to start, transformers start matlab simulation, we hope to help)

：首先介绍了系统辨识的基本原理，简要介绍了Matlab中系统辨识 的实现方法。并结合具体的例子，显示Matlab系统辨识工具箱在系统辨 识中的强大功能和辨识快速准确等优点。(This paper introduces the basic theory of System Identification，the realization method in Matlab and presents the strong function of System Identification toolbox with the merit of fast，precision and SO 011 by an example．)

说明：  电缆阻抗求取程序，高频电缆串联阻抗，根据高频中压电缆模型建立，(Cable impedance calculation program)

一个基于阈值的粒子比较准则，用于处理多目标约束优化问题,该准则可以保留一部分序值较小且约束违反度在允许范围内的不可行解微粒,从而达到由不可行解向可行解进化的目的；一个新的拥挤度函数,使得位于稀疏区域和Pareto前沿边界附近的点有较大的拥挤度函数值,从而被选择上的概率也较大 从而构成解决多目标约束优化问题的混合粒子群算法。(A comparison based on the threshold criteria for the particle to handle multi-objective constrained optimization problem, part of the guidelines can keep order value is small and the constraint violation in allowing infeasible solutions within the particles, so as to achieve a feasible solution to the infeasible solution The purpose of evolution a new function of crowding, making the Pareto front in the sparse region and near the border points have a greater value of the congestion function, which is the larger the probability of selection so as to constitute solve multi-objective constrained optimization problems hybrid particle swarm algorithm.)