Hirose FH26-33S-0.3SHW.pdf

神经网络与深度学习案列代码，神经网络与深度学习教程例题代码(Neural Network and Deep Learning Case Code, Neural Network and Deep Learning Course Case Code)

说明：  s7-1200 modbus tcp 通讯，1200PLC做服务器，(Modbus TCP/IP Server)

PSD-BPA实例，联网丰大典型例子，包括云南和红河网架(PSD-BPA example, a typical example of networking, including the Yunnan and Honghe grids)

MSP430实现的红外全双工通信，能稳定进行数据传输，适合短距离通信应用。(MSP430 infrared achieve full-duplex communication, data transmission can be stable for short-range communications applications.)

delphi写的钢材进销存源码,符合钢材行业的销售模式-delphi write ADOMS steel source, in line with the steel industry sales model

应用背景用于大学51单片机课程设计，数码管显示时间，设置闹铃，电子钟，显示时间、日期，秒表用于计时，用于51单片机关键技术AT89S52单片机电子钟（含万年历、闹铃、秒表）有注释，可以删除部分功能，所有功能都采用子函数，采用8位数码管显示，采用8位IO口独立式按键输入。涵盖电子钟所有内容。

采用极大极小算法的苏拉卡尔塔棋C语言编程(Sura C programming language using minimax algorithm)

用于计算双质点扭振，可计算共振点及一定频率范围内的传递比(Calculation of Torsional Vibration, Resonance and Transfer Ratio of Two Particles)

说明：  双向八车道高速公路合流区最大交通流率计算(Calculation of the maximum traffic flow rate in the confluence area of two-way eight Lane Expressway)

说明：  针对实际对象数学模型不明确而难以控制的问题,采用人工免疫网络的离散模 型与学习算法,将人工免疫系统与神经网络结构的优势相结合,提出了一种基于人工免疫 网络的模式识别算法,构造了对象识别的人工免疫网络模型.该算法综合了网络节点的定 位与参数调整以及对基函数的平滑因子实施调谐等功能,有效地解决了径向基函数 (RBF)神经网络模式识别的两个阶段任务,使模式识别的精度有较大的改进.采用两个不 同对象函数进行的仿真试验表明,该算法具有快速收敛性与较高的准确性. (Mathematical model for the actual object is not clear and difficult to control the problem, the use of artificial immune network model and the discrete learning algorithm, artificial immune systems and neural networks combine the advantages of structure, an artificial immune network based on pattern recognition algorithms, Construction of the object identified by artificial immune network model. the algorithm is a combination of network nodes to adjust the position and parameters as well as the basis function implementation of the smoothing factor, tuning and other functions, to effectively solve the Radial Basis Function (RBF) neural network pattern recognition of two phase of the task, so that the accuracy of pattern recognition have greater improvements. the use of two different object functions of the simulation tests show that the algorithm has fast convergence and higher accuracy.)