61046606ABCNNTrain

steps - 1. run DigitRecognizer.m 2. mode to run a. Test Mode input pad will open with axes having a red dot. left-click mouse and drag(dont unclick) mouse to draw a numeric digit. if you unclick mouse it won t draw anything. if you want to continue drawing, click again on any red place on axes and start dragging. once done, click submit. it will give you result. b. Training Mode input pad will open with axes having a red dot. draw a number and click submit. when promted, enter the value you drawn. if you wish to continue training, click YES and repeat. if you click No, a feedforward neural network will be trained and saved, you can test it.

wireless sensor network localization estimation using distance vector one hop

matlab下实现kaplan算法，测量心率变异性特征的文件，包括谱分析工具(Matlab under kaplan algorithm, measuring heart rate variability characteristics of the document, including spectral analysis tools)

说明：  含分布式电源的半不变量法概率潮流计算程序(Probabilistic Power Flow Computing Program Based on Semi-invariant Method)

自己开发的基于阶跃响应曲线的面积法程序，实验结果良好。(Their own development based on the step response curve area method procedures, the experimental results well.)

应用matlab进行粒子滤波在无线传感器中的目标追中的仿真(Application of the particle filter matlab wireless sensors in the simulation of target tracking)

功能代码含多种QoS约束的组播路由问题遗传模拟退火算法通用MATLAB源码.(multicast)

该算法使用扩展卡尔曼滤波提议的分布模型，来改进粒子滤波(The algorithm uses the extended Kalman filter distribution model proposed to improve particle filter)

TolPac=1 输入数据块数 PacketLen=10 每块的符号数目 M=64 调制指数 SNR=20 NFFT=256 Length of IFFTCpLength=16 Length of Prefix NSubc=64 Number of subcarriers freoff=0.5 归一化频偏2.25,phaseoff=0.1 (TolPac = 1 input data blocks the the PACKETLEN 10 of the span per block, the number of symbols M = 64 modulation index SNR = 20 NFFT = 256 the length of IFFTCpLength = 16 Length of Prefix NSubc = 64 Number of subcarriers freoff = 0.5 the normalization frequency offset 2.25 phaseoff = 0.1 )

基于 汽车跟驰模型OVM 和 IDM 的动态特性分析（2辆车）(Dynamical Characteristics of OVM and IDM Using Two Car Simulation for two vehicles.)