severalderivationschemeofHyperbolicequations

直接转矩控制方面的例子，希望能给大家提供帮助(Examples of direct torque control, hope that they can help)

matlab_fuzzymeasure fuzzymeasure

QWT code for Disparity Estimation.

人工智能计算 利群算法，particle swarm algorithm PSO ,去求解函数的最小值及其对应的根(AI computing- ABBA algorithms, particle swarm algorithm PSO, to solve the root of the minimum and the corresponding function)

final的重要性和和本质的定义及区别，让你熟练的掌握final的用法。(and the final of the importance and nature of the definition and distinction between)

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。 BP（Back Propagation）神经网络是1986年由Rumelhart和McCelland为首的科学家小组提出，是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hidden layer)和输出层(output layer)。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm. BP (Back Propagation) neural network is a 1986 team of scientists headed by Rumelhart and McC)

小波变换（wavelet transform，WT）是一种新的变换分析方法，它继承和发展了短时傅立叶变换局部化的思想，同时又克服了窗口大小不随频率变化等缺点，能够提供一个随频率改变的“时间-频率”窗口，是进行信号时频分析和处理的理想工具。它的主要特点是通过变换能够充分突出问题某些方面的特征，能对时间（空间）频率的局部化分析，通过伸缩平移运算对信号（函数)逐步进行多尺度细化，最终达到高频处时间细分，低频处频率细分，能自动适应时频信号分析的要求，从而可聚焦到信号的任意细节，解决了Fourier变换的困难问题，成为继Fourier变换以来在科学方法上的重大突破。(wavelet transform)

图像的基于8*8分块的DCT变换编码 MATLAB编程环境 (Images based on 8* 8 block of DCT transform coding MATLAB programming environment)

GLOBAL OPTIMIZATION ALGORITHM

ART2网络的MATLAB程序，自己编写的。最近一系列的文章都是用这个作的实验。在科学网可以找到本人博客下载相关论文(ART2 network MATLAB procedures, I have written. The recent series of article are made using this experiment. Net can be found at science blog I download related thesis)