makeJac

一个经典的分块DCT数字图像水印算法 嵌入 提取(A classical DCT block of digital image watermark embedding algorithm extracts)

matlab程序，用于求时间序列的hurst指数，判断数据的长程关联性。 (the matlab procee for calculating the Hurst Exponent for a time series data--Hurst Exponent)

it is a code for denoising based on singular value decomposition. it is a rank reduction based method

基于matlab的爬山法光伏并网逆变器最大功率跟踪模型(Matlab-based mountain climbing photovoltaic maximum power tracking inverter model)

Lab 2 – Synthesizable MATLAB This lab exercise will explore the effects that different MATLAB coding styles have on hardware. The lab has two parts, each of which begins with a short introduction. This lab exercise is based on the simple MATLAB FIR filter model shown below:(Lab 2- Synthesizable MATLABThis lab exercise will explore the effects that different MATLAB coding styles have on hardware. The lab has two parts, each of which begins with a short introduction. This lab exercise is based on the simple MATLAB FIR filter model shown below:)

关于图像恢复的程序。输入恢复类型、待恢复图像的相关文件（程序中具体列出）和图像数量即可恢复出原图像和恢复情况评估。(With regard to the procedures for image restoration. Enter the recovery type, you can restore the image file to be restored (specifically listed in the program) and the number of images of the original image and restore the situation to assess.)

0_Linear：线性回归练习 1_LogistRegression：逻辑回归练习 2_boston：波士顿房价预测 3_regularization：正则化 5_stock：股票价格预测 6_CTR：点击率预测 7_all_model：回归与分类模型 8_muticlass：多分类练习 9_regression_implement：不同回归算法tf实现(0_Linear. 1_LogistRegression. 2_boston. 3_regularization. 5_stock. 6_CTR. 7_all_model. 8_muticlass. 9_regression_implement.)

说明：  近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。 多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence. The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)

用matlab编写的一些经典差分算法，很实用(Using matlab to prepare some of the classic differential method, it is useful)

在理想的信道状态条件下，对MIMO-OFDM系统进行仿真，包括信道估计，调制，解调，信道编解码等(In an ideal channel state conditions, the MIMO-OFDM system is simulated, including channel estimation, modulation, demodulation, channel coding and decoding)