solving-equation

萤火虫算法（Firefly Algorithm）是一种群智能优化算法，它是英国的学者在2008年提出的，其本质是利用萤火虫在觅食和信息交汇中的一种仿生算法。( Firefly Algorithm (Firefly Algorithm) is a swarm intelligence optimization algorithm, which is a British scholar proposed in 2008, and its essence is to use the firefly in the convergence of information and foraging in a bionic algorithm.)

说明：  多目标遗传算法在工程领域应用较为广泛，希望对大家有用。(Key procedures of multiobjective optimization with elite decision)

DOUBLY FED INDUCTION MACHINE SIMULATION

matlab在科学计算中的应用，计算，matlab，代码，程序，运行结果(matlab in scientific computing, computing, matlab, code, program, the results)

稳压电源，十分创新的文件，大家没事可以看看(Regulated power supply, a very innovative paper, we can see nothing)

基于模型的设计 利用tlc编写设备驱动代码用于代码自动生成(Tlc to write device driver code for automatic code generation model-based design)

说明：  高斯过程(GP)模型中推理和预测的实现。它实现了在《Rasmussen & Williams:机器学习的高斯过程》(麻省理工学院出版社，2006)和《Nickisch & Rasmussen:二进制高斯过程分类的近似》(JMLR, 2008)中讨论的算法。该函数的优点在于灵活性、简单性和可扩展性。该函数具有一定的灵活性，首先通过定义均值函数和协方差函数来确定遗传算法的性质。其次，它允许指定不同的推理过程，如精确推理和期望传播(EP)。第三，它允许指定似然函数，如高斯函数或拉普拉斯函数(用于回归)和累积逻辑函数(用于分类)。简单性是通过一个简单的函数和紧凑的代码实现的。可扩展性是通过模块化设计来保证的，允许为已经相当广泛的推理方法、均值函数、协方差函数和似然函数库轻松添加扩展。(Gaussian Processes for Machine Learning , the MIT press, 2006 and Nickisch & Rasmussen: Approximations for Binary Gaussian Process Classification , JMLR, 2008. The strength of the function lies in its flexibility, simplicity and extensibility. The function is flexible as firstly it allows specification of the properties of the GP through definition of mean function and covariance functions. Secondly, it allows specification of different inference procedures, such as e.g. exact inference and Expectation Propagation (EP). Thirdly it allows specification of likelihood functions e.g. Gaussian or Laplace (for regression) and e.g. cumulative Logistic (for classification). Simplicity is achieved through a single function and compact code.)

用MMSE LMS Wiener-Hopf三种方法补偿QPSK调制信号在非理想信道的源代码(MMSE LMS and Wiener-Hopf solutions to QPSK modulated signal transmitting through non-ideal channel)

详细介绍了编码原理的基础知识，是编程的入门级必备教材(Details the basics of coding theory, is an essential textbook entry-level programming)

运用shancen格子玻尔兹曼模型模拟两相分离，验证可行(Use shancen lattice Boltzmann model to simulate two-phase separation, verification feasible)