Prg

采用神经网络实现手写识别的一种方法，建立Bp神经网络，采用快速训练方法，可快速完成一类相关手写字体的模式识别，识别率较高，当字体变化较大识别率降低时，可重新训练具有较强的适应性。实验证实本方法较好实现了手写字符识别，但也存在识别速度较慢，有时训练不收敛等缺点(Handwriting recognition using neural network is a way to establish Bp neural network, using fast training methods, and can be related to the completion of a class of handwriting pattern recognition, recognition rate higher recognition rate when the font changed greatly reduced, they can re- Training has strong adaptability. Experiments confirmed that this method achieved a better handwritten character recognition, but there are also identified slow, and sometimes non-convergence of the training deficiencies)

PID controller GUI for understanding the effect of gains

matlab编写的遗传算法优化程序，编译对目标函数进行优化(matlab genetic algorithm to optimize the preparation procedures,)

维纳滤波器（Wiener filter）是由数学家维纳（Rorbert Wiener）提出的一种以最小平方为最优准则的线性滤波器。在一定的约束条件下，其输出与一给定函数（通常称为期望输出）的差的平方达到最小，通过数学运算最终可变为一个托布利兹方程的求解问题。维纳滤波器又被称为最小二乘滤波器或最小平方滤波器，目前是基本的滤波方法之一。(Wiener filter (Wiener filter) is caused by a mathematician Wiener (Rorbert Wiener) proposed guidelines for the minimum square optimal linear filter. Under certain constraints, which outputs a given function (often called the desired output) reaches the minimum squared differential, the final mathematical operation may become a problem solving Equation Leeds Taub. Wiener filter is also known as the least squares filter or least squares filter, currently one of the basic filtering methods.)

this code is used to implement FMT Filter bank trancsiver in matlab. the filter coefficient can be changed also the number of subcarriers.

AdaBoost元算法属于boosting系统融合方法中最流行的一种，说白了就是一种串行训练并且最后加权累加的系统融合方法。 具体的流程是：每一个训练样例都赋予相同的权重，并且权重满足归一化，经过第一个分类器分类之后， 计算第一个分类器的权重alpha值，并且更新每一个训练样例的权重，然后再进行第二个分类器的训练，相同的方法....... 直到错误率为0或者达到指定的训练轮数，其中最后预测的标签计算是各系统*alpha的加权和，然后sign（预测值）。 可以看出，训练流程是串行的，并且训练样例的权重是一直在变化的，分错的样本的权重不断加大，正确的样本的权重不断减小。 AdaBoost元算法是boosting中流行的一种，还有其他的系统融合的方法，比如bagging方法以及随机森林。 对于非均衡样本的处理，一般可以通过欠抽样(undersampling)或者过抽样(oversampling)，欠抽样是削减样本的数目， 过抽样是重复的选取某些样本，最好的方法是两种进行结合的方法。 同时可以通过删除离决策边界比较远的样例。 (AdaBoost boosting systems dollar fusion algorithm is the most popular one, it plainly systems integration approach is a serial train and final weighted cumulative. Specific process is: Each training example is given equal weight, and the weights satisfy normalization, after the first classifiers after Calculating a first classifier weights alpha value for each sample and updates right weight training, and then the second classifier training, the same way ....... 0, or until the specified error rate training rounds, wherein the label is the calculation of the final prediction system* alpha weighted and then sign (predicted value). As can be seen, the training process is serial, and weight training examples is always changing, the right of the wrong sample weight continued to increase, the right to correct sample weight decreasing. AdaBoost algorithm is an element, as well as other methods of boosting popular systems integration, such as bagging and random forest method. For )

PPM调制的超宽带系统RAKE接收机的误码率仿真程序(BER simulation of PPM_UWB system)

this will help in connecting dsp board with matlab through the IDE

响应面法计算相关系数情况下结构的可靠度.已知极限状态方程，变量服从对数正态分布，变量均值和标准差已知，且知道变量的相关系数。(Response surface methodology to calculate the correlation coefficient of reliability under the circumstances structures known to limit state equation, variables lognormal distribution, the mean and the standard deviation is known variables, and that the correlation coefficient variables.)

This code is for solving traveling salesman problem using ant colony algorithm.Ant Colony Optimization (ACO) is a population-based approach for solving combinatorial optimization problems that is inspired by the foraging behavior of ants and their inherent ability to find the shortest path a food source to their nest.