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Programmingproblem
- 这是用matlab实现无约束优化\\线性规划\\非线性规划等规划问题的基本实现例子-This is achieved using Matlab unconstrained optimization \\ linear programming \\ planning nonlinear programming problem is the basic Examples are
minSimpSearch
- 非线性最小二乘优化问题，经过试验很好用，有兴趣的可以-Nonlinear least squares optimization problem, after a test is useful, who are interested can try
C_language_algorithms_for_Quick_Lookup_Manual
- 《C语言算法速查手册》用C语言编写了科研和工程中最常用的166个算法，这些算法包括复数运算、多项式的计算、矩阵运算、线性代数方程组的求解、非线性方程与方程组的求解、代数插值法、数值积分法、常微分方程（组）初值问题的求解、拟合与逼近、特殊函数、极值问题、随机数产生与统计描述、查找、排序、数学变换与滤波等。同时结合这些算法列举了将近100个应用实例，对其进行验证和分析。 -" C language algorithms for Quick Fact Manual" using
mastering_matlab
- 精通MATLAB最优化计算 配套光盘 本书的主要内容是应用MATLAB来解决最优化问题，通过将“最优化问题”、“MATLAB优化工具箱”和“MATLAB编程”这三方面有机结合进行讲述，即一方面是使用工具箱来快速解决最优化问题，另一方面是通过算法编程深入解决最优化问题。主要包括MATLAB优化工具箱、无约束多维极值问题、约束优化问题、非线性最小二乘优化问题、线性规划、整数规划、二次规划、粒子群优化算法、遗传算法。 -The main contents of the book is the
mtl_reg_sim_complinearized
- 多元非线性回归——岭回归方法，比常规的最小二乘更适合数据量较大的优化问题-Multiple nonlinear regression- ridge regression method is more suitable than the conventional least squares optimization problem of the large amount of data
matlab--jie-fang-cheng-zu
- 非线性方程组的求解是一个很麻烦的问题，应该对某一类方程组进行matlab求解-Nonlinear equations is a very troublesome problem, it should be of a certain type equations matlab solving
LFM
- 针对贝叶斯滤波过程中存在的目标跟踪问题，提出几种典型的贝叶斯滤波方法，如EKF, UKF, PF和UPF 等，基于这些方法所构 建的框架，对它们进行性能测试和比较，并在非线性环境下，讨论这些方法的特点，仿真实验结果表明，在非线性非高斯环境下，UPF 方 法的性能是最优的。 -According to the bayesian filtering occurred in the process of target tracking problem, this paper puts forw
feixianxingzuixiaoerchengyouhua
- 用G-N法求解非线性最小二乘优化问题 用修正G-N法求解非线性最小二乘优化问题 用L-M法求解非线性最小二乘优化问题 -GN method for solving nonlinear least squares optimization problems using a modified GN method for solving nonlinear least squares optimization problems using LM method for solving non
Simulink_Files_DPD
- Nonlinear Distortion in Wireless Systems: Modeling and Simulation with Matlab一书中的源代码simulink文件.-This book covers the principles of modeling and simulation of nonlinear distortion in wireless communication systems with MATLAB® simulations and tec
svm
- 支持向量机模型用于预测分析效果显著，它在解决小样本、非线性及高维模式识别中表现出许多特有的优势，并能够推广应用到函数拟合等其他机器学习问题中-Support vector machine model is used to predict significant effect in solving small sample, nonlinear and high dimensional pattern recognition exhibit many unique advantages, and
neural-network
- 基于BP神经网络的非线性分类，及运用其解决异或问题，并对Iris数据进行分类-Nonlinear classification based on BP neural network and the xor problem, and its appplication on the data of Iris.
davidscherer-glowscript-c1d642e5b217
- magnetic field strength, making this approach unsuitable for deep space missions, and also more suitable for low Earth orbits as opposed to higher ones like the geosynchronous. The dependence on the highly variable intensity of Earth’s magnetic
PSO-MC
- PSO算法和蒙塔卡洛算法的混合算法，求解非线性方程组。单目标优化问题-Hybrid algorithm of PSO and Monta Carlo algorithms for solving nonlinear equations. Single-objective optimization problem
minlp
- Solves the mixed integer nonlinear problem:
Improved_SMCPHD
- 该算法基本思想是利用一组带有相应权值的随机样本即粒子去逼近PHD分布和基数分布，其意义在于不仅解决重积分计算没有闭式解的难题，而且在滤波过程中，PHD函数被一系列离散的带权值的样本近似，随着样本粒子数量的增加，PHDF接近于Bayes最优估计，而且不受模型线性和高斯假设的限制，可以适用于非线性非高斯的随机系统。-The algorithm the basic idea is to use a set of random sample with the corresponding weight n
mvrvm_matlab
- 多维支持向量机 可以解决小样本情况下的机器学习问题。可以提高泛化性能。可以解决高维问题。可以解决非线性问题。可以避免神经网络结构选择和局部极小点问题。-Multidimensional support vector machine can solve the problem of machine learning small sample case. You can improve the generalization performance. You can solve high-dimens
ceemdan
- CEEMDAN方法，用于解决EMD分解过程中的模态混叠问题，同常用的EEMD方法相比，其有效减少了迭代次数，增加了重构精度，更加适合非线性信号的分析。(CEEMDAN method is used to solve the modal aliasing problem in the EMD decomposition process. Compared with the commonly used EEMD method, it effectively reduces the number of