colornoise

用LCS方法解决字符匹配问题，用到动态规划的思想。原创(LCS solution with matching characters, the idea of using dynamic programming)

地震信号处理接收函数讲已处理好的程序进行作图(Speak seismic signal processing receiver function plotting program has been handled well)

系统辨识，节拍延迟线（TDL）模型，PRN序列，蒙特卡洛仿真次数(System identification, beats delay line (TDL) model, PRN sequences, Monte Carlo simulation times)

solemnization: Finding the skeleton in the given image which can be use in many application such as object detection by combining it with some methods such as region growing

阐述了负荷预测的应用研究,用MATLAB实现动态聚类或迭代自组织数据分析，采用了小波去噪的思想，多抽样率信号处理，利用自然梯度算法，预报误差法参数辨识-松弛的思想，进行逐步线性回归，从先验概率中采样，计算权重。( It describes the application of load forecasting, Using MATLAB dynamic clustering or iterative self-organizing data analysis, Using wavelet denoising thought, Multirate signal processing, Use of natural gradient algorithm, Prediction Error Method for Parameter Identification- the idea of relaxation, Stepwise linear regression, Sampling a priori probability, calculate the weight.)

说明：  粒子群优化算法(Particle Swarm optimization,PSO)又翻译为粒子群算法、微粒群算法、或微粒群优化算法。是通过模拟鸟群觅食行为而发展起来的一种基于群体协作的随机搜索算法。通常认为它是群集智能 (Swarm intelligence, SI) 的一种。它可以被纳入多主体优化系统(Multiagent Optimization System, MAOS)。粒子群优化算法是由Eberhart博士和kennedy博士发明。(The probabilistic neural network has a simple structure and is easy to design Particle Swarm Optimization (PSO) is translated as Particle Swarm Optimization, Particle Swarm Optimization, or Particle Swarm Optimization. It is a random search algorithm based on group collaboration developed by simulating the foraging behavior of birds. It is generally considered to be a type of swarm intelligence (SI). It can be incorporated into Multiagent Optimization System (MAOS). The particle swarm optimization algorithm was invented by Dr. Eberhart and Dr. Kennedy.)

国外的基于MATLAB的分割算法，比较详细，有样图，需要的可以看看(Abroad, the segmentation algorithm based on MATLAB, more detailed, drawing, and we need to look at)

analyzes the power systems in normal steady-state operation. There exist a number of software implementations of power flow studies.

自己编写的模拟退火粒子群算法，里面含有测试函数，比较简单，适合初学者。(I have written simulated annealing particle swarm algorithm, which contains a test function is relatively simple, suitable for beginners.)

预测分类，针对目标样本进行训练比对，预测有可能发生的情况(Predictive classification, target training samples compared to predicted situation may occur)