java编程思想，想成为JAVA程序员必看的一本书。

用C++实现的简易终结者小游戏，可以运行， 不过功能很简单-C++ implementation of the simple Terminator game

C# XML序列化源码-C# XML serialization FOSS

测试信号源 labview程序-Labview signal source testing procedures. . . . . . . . . . . . . . .

C++学习随笔-C++STADY

组策略的详细介绍，不用依赖软件来设置控制电脑的魔法设置。希望对你有用-A detailed description of Group Policy, do not rely on computer software to set up control magic settings. Hope that useful to you

带LCD驱动纳瓦级mpu pic16F946 ad采样程序-with LCD driver Navarro-mpu pic16F946 ad sampling procedures

GTRACK Track mouse position and show coordinates in figure title. Once GTRACK is active the mouse position is constantly tracked and printed on the current figure title. A left-click will print the coordinates in the command line and store them. Clicking the mouse right button deactivates GTRACK.

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,

可以方便转换ASCII及十六进制和十进制之间转换，适用于编程新手的方便工具-Can easily convert ASCII and hexadecimal and decimal conversions between, apply a handy tool for novice programmers

对于汉诺塔，大家一点不陌生，这是我数据结构的一个作业，里面讲的很详细-The Tower of Hanoi, is no stranger to everyone, this is my data structure of a work, which stresses the very detailed