基于遗传算法的BP算法

该方程计算任意数据的经验正交函数（EOF）(this function calculates the EOF of any dataset)

搜寻最短延时的交织m序列伪码，可选择m序列的长度，自动产生生成多项式-Search for the shortest delay interwoven m PN sequence can choose the length of m sequence, automatically generating polynomial

说明：  Vumat subroutine fo simulation of brittle fracture

说明：  这是偶然在网上找到的利用神经网络做2018年电力负荷预测的matlab代码，分享给大家。(This is the matlab code that I found by chance on the Internet to use 2018 neural network power load forecasting and share it with everyone.)

计算三电平逆变器出现的中点电位波动问题分析-caculate NPC circuit netural current balance problem

NEC红外编码，IO模拟，C51程序，使用在一个双向DVD系统中，通过遥控器查看播放信息，和控制播放等。-NEC infrared codes, IO simulation, C51, the use of the DVD in a two-way system, Remote View through broadcast information, and control shows.

大学C++ 课程 模板PDF版 授课内容 详细(University C++ course template PDF version taught detailed)

《The Little SAS Book 中文版》以大量实例、清晰简明的解释以及尽可能少的术语来介绍SAS语言，且大部分的功能均来自Base SAS。Base SAS包含了所有程序员所使用的核心功能。(The Little SAS Book Chinese Edition introduces SAS language with a large number of examples, clear and concise explanations and as few terms as possible, and most of its functions come from Base SAS. Base SAS contains the core functions used by all programmers.)

dds->9954的pcb供大家参考,这个扳子我调通了的可以放心开办-dds-

在机动目标跟踪中，机动目标模型是机动目标跟踪的基本要素之一，一般希望机动目标模型能准确表征目标机动时的各种运动状态。比较常用的模型有匀速运动(CV)模型、匀加速运动(CA) 模型、时间相关模型（Singer）和机动目标“当前”统计模型。上述模型均采用机动频率表征目标的机动情况。在应用当中，通常采用固定的机动频率，这就表示机动目标的机动时间是一定的，而实际上机动目标的机动时间是不断变化的，也就是说机动频率是不断变化的，采用固定机动频率必然会带来误差。采样周期在0.5―2S时，机动频率越小跟踪精度越高[1]，但机动频率仍然是固定值。本文提出的基于神经网络的机动频率自适应调整方法可以使机动频率随机动而变化，从而提高状态估计的准确性，提高跟踪精度。本文将小波神经网络用于机动目标跟踪中机动频率的自适应调整，该算法对机动目标“当前”统计模型中的机动频率进行实时修改, 从而自适应的改变机动频率,使跟踪算法与目标的真实状态更接近。该算法采用小波神经网络的离线训练，实时性好。-The maneuver of the maneuvering target is uncertain. The maneuvering frequency is constantly changeable, but traditionally it is beforehand determined as a constant based on the target state estimation in the state model of the maneuvering target. The maneuver of the maneuvering target makes the kinematics equation of the target model mismatch with the practical motion model and the tracking error will be increased. Based on the advantages of the self-learning, the rapid convergence rate and the nonlinear approximation ability of the wavelet neural network,