add-new-toolbox-in-matlab

15名基督教徒和15名异教徒同乘一船航行，途中风浪大作，危机万分，领航者告诉大家，只要将全船的一半人投入海中，其余人就能幸免。大家都同意这个办法，并协定者30人围成一圈；由第一个人起报数，每数至第9人便把他投入海中，下一个接着从1开始报数，第9人又被投入海中，依次循环，直至剩下15人为止。问题是如何排法使投入海中的人全为异教徒？(15 Christians and pagans 15 vessels with one by the way, big waves, extreme crisis, leader told everyone that as long as will be half the person boat into the sea, and the remaining person will be able to escape. We all agree that this approach, and agreements were 30 form a circle from the first reported from a few individuals, the number to 9 for each person put him into the sea, then from the next one to start off, 9 people have been invested in the sea, followed by cycle, until the remaining 15 people so far. The question is how to row Act so that the person into the sea all infidels?)

Mathematic Algorithm for image filter High Medium and Less

audio watermarking embedding and exctract

Ebook - Current sensing for energy metering

语音采集加噪声程序 语音端点检测 已经调试很好用 (The voice acquisition plus the speech endpoint detection of the noise program debugging has been very good, )

PID控制算法简单、鲁棒性强，但其参数整定过程繁琐，整定时需要控制对象的精确数学模型，而且整定往往是针对某一种具体工况进行的，缺乏自学习和自适应能力。模糊神经网络则兼备了模糊逻辑和神经网络的优点，具有函数逼近功能，具有较强的自适应、自学习能力、容错能力和泛化能力。借助于遗传算法对全局性参数进行优化设计，借助于BP算法对局部性参数进行优化，将模糊神经网络和遗传算法引入PID控制参数的整定过程，构造出一种基于模糊神经网络和遗传算法的智能PID控制器(Intelligent controller based on fuzzy neural network and genetic algorithm)

反馈网络是神经网络的基础 这里提供了神经网络中用到的反馈 这里能充分理解文档的内容就能很好的掌握神经网络的基础。我将各个函数写成了不同的文档 就是便于大家理解。(Feedback network is the basis of the neural network here provides feedback neural network is used here to fully understand the content of the document can very good master the basis of neural network. I will each different function in the form of a document is easy to understand.)

Computational Electromagnetics for RF and Microwave Engineering

说明：  快速迭代收缩阈值算法，FISTA用一种更为聪明的办法选择序列{xk}，使得其基于梯度下降思想的迭代过程更加快速地趋近问题函数F(x)的最小值。FISTA的缺点是：Lipschitz常数L(f)不一定可知或者可计算。(Fast iterative contraction threshold algorithm, FISTA uses a more clever method to select the sequence{xk}, making its iterative process based on the gradient descent idea more quickly approach the minimum value of the problem function F(X). The disadvantage of FISTA is that the Lipschitz constant L(f) is not necessarily known or computable.)

Matlab, Simulink, and a Communications Example