Project-Learn-English

通过蒙塔卡罗搜索方法反解坐标变换里的参数的方法(Monta Carlo search method inverse solution coordinate transformation parameters)

使用强化学习方法实现移动激光测距机器人避障(Realization of obstacle avoidance by mobile laser rangefinder using Reinforcement learning method)

分析了该信号的时域、频域、倒谱，循环谱等,结合PCA的尺度不变特征变换(SIFT)算法，DC-DC部分采用定功率单环控制。( Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. Combined with PCA scale invariant feature transform (SIFT) algorithm, DC-DC power single-part set-loop control.)

得到一些列的离散数据，用matlab，进行曲线拟合(Get some out of discrete data with matlab, for curve fitting)

迭代法求解一次方程运用迭代法实现一次方程的求解 原创(Iteration method to solve a equation)

this file describes and run the HALFTONING of a picture.

Tracking of visual phenomena is hard. Very, very hard. And frustrating. You should try not to get discouraged by poor tracking results, but rather concentrate on the specific reasons why your tracker may not be performing well. Is the bad performance predictable from the theoretical properties of the tracker? If so, that s a valuable observation that will serve you well in the future

this source code is chp6ex14 matlab

电磁场空间场强统计分析源代码，主要分析场强的随机性和统计性(micwave )

说明：  the matlab hopfild for tsp question