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matlab Financial Derivatives工具箱的学习书籍(matlab Financial Derivatives Toolbox learning books)

a matlab function that can do many fuction on drowing

Z N法进行PID控制，采用simulink进行仿真，得到最优控制参数，属于工程上的参数整定 (Z N method for PID control, using simulink simulation, get the optimal control parameters, belong to the engineering parameter setting )

esp8266 iot源码包含at指令和smartconfig demo(esp8266 iot_demo)

多重分形去趋势交叉相关性分析，分析时间序列，如股市变动价格，PM2.5数据，外币汇率等(Multifractal detrending cross correlation analysis and analysis of time series, such as stock market variable price, PM2.5 data, foreign currency exchange rate, etc.)

高斯消元法程序，高斯消元法程序11111111(高斯消元法程序)

产生真实运动轨迹的程序-系统在建模的时候，可以用一个确定的状态方程表述出，不存在有随机量。(To have a real trajectory of the process- system in the modeling, they can identify with a state equation formulation that does not exist there is a random quantity.)

In this paper, we present an improved and discrete version of the Cuckoo Search (CS) algorithm to solve the famous traveling salesman problem (TSP), an NP-hard combinatorial optimisation problem.

决策树源代码，用matlab语言编写的，适用于分类及相关问题的分析(Decision tree source code, written with matlab language, suitable for classification and analysis of the related problem)

本书是The IMA Volumes in Mathematics and its Applications系列的一本，由Springer-Verlag发表，用于交流每年数学规划算法方面的新成果，希望对于广泛的科学团体有帮助。 许多工程，运筹，和科学应用包括离散或连续的决策变量，以及这些决策变量的非线性关系。这种 Mixed-integer nonlinear programming （MINLP，混合整数非线性规划），兼具来自非线性问题的非凸函数优化，以及来自整数的离散优化，这两方面的挑战。这种问题是优化问题里面建模最灵活的类型之一，但是因为它范围极广，在最一般的情况下，它是几乎无法解的。然而，日渐壮大的研究者和程序员队伍，包括化学工程，运筹研究者，工业工程师，机械工程师，经济学家，统计学家，计算机科学家，运营经理，和数学程序员，都对求解大规模MINLP问题产生兴趣。(Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners ― including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers ― are interested in solving large-scale MINLP instances.)