digital_process

说明：  单纯形法matlab程序，输入A,b,c，得到整个过程的单纯形表与最优解，最优值，每一步变换的单纯形表都有给出，完全没有错，很详细，有运行结果说明。(The simplex method matlab program, input A, B, C, get the simplex table and the optimal solution of the whole process, the optimal value, the simplex table of each step transformation are given, there is no error at all, very detailed, there are running results.)

线性方程组的迭代解法解法，里面有三种不同的源程序，在matlab2008中测试通过！！(Linear equations of the iterative solution method, there are three different types of source code, adopted in matlab2008 test! !)

可以做出一个漂亮的三维心形，赶快快来试试吧(Can make a beautiful three-dimensional heart-shaped, come try it)

小波包的数字水印watermarking (watermarking )

MATLAB求音频短时能量，可以快速用matlab获取音频短时能量(MATLAB and audio short-term energy, you can quickly matlab audio short-term energy)

语言：matlab 实现功能：逻辑回归实现分类 输出：predict_label;ACC(Language: matlab Implementation function: Logistic regression implementation classification Output: predict_label; ACC)

电力负荷预测是电力系统规划的重要组成部分，也是电力系统经济运行的基础，其对电力系统规划和运行都极其重要。利用粒子群算法优化支持向量机更加高效准确预测电力负荷。(The power load forecasting is an important part of the power system planning, and it is also the basis of the economic operation of the power system. It is very important to the planning and operation of the power system. Particle swarm optimization is used to optimize SVM to predict power load more efficiently and accurately.)

粒子群算法，用matlab实现，内含几个测试参数。(Particle swarm optimization with matlab realize that contains several test parameters.)

训练集/测试集产生 load spectra_data.mat 随机产生训练集和测试集 temp = randperm(size(NIR,1)) 训练集——50个样本 P_train = NIR(temp(1:50),:) T_train = octane(temp(1:50),:) 测试集——10个样本 P_test = NIR(temp(51:end),:) T_test = octane(temp(51:end),:) N = size(P_test,2) 数据归一化 ( Training set/test set generation load spectra_data.mat randomly generated training set and test set temp = randperm (size (NIR, 1)) training set- 50 samples P_train = NIR (temp (1:50) ,:)' T_train = octane (temp (1:50 ),:)' test set- 10 samples P_test = NIR (temp (51: end ),:)' T_test = octane (temp (51 : end ),:)' N = size (P_test, 2) Data Normalization)

MATLAB® is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numeric computation. Using the MATLAB product, you can solve technical computing problems faster than with traditional programming languages, such as C, C++, and Fortran. You can use MATLAB in a wide range of applications, including signal and image processing, communications, control design, test and measurement, financial modeling and analysis, and computational biology. Add-on toolboxes (collections of special-purpose MATLAB functions, available separately) extend the MATLAB environment to solve particular classes of problems in these application areas. MATLAB provides a number of features for documenting and sharing your work. You can integrate your MATLAB code with other languages and applications, and distribute your MATLAB algorithms and applications.