MOGWO

曲线的卡尔曼滤波程序仅供参考。谢谢大家的支持。要是好的话多支持我啊(good)

MATLAB的教程 简单明了 适合初学者 及其相应的实验(Simple MATLAB tutorial for beginners and their corresponding experimental)

说明：  MH背包公钥密码算法的实现 MH背包公钥密码算法的实现(MH knapsack public key cryptographic algorithm realization MH knapsack public key cryptographic algorithm realization)

This function stretch and scale image histogram

说明：  用于无线通信中天线仿真，matlab上的源代码，第四部分。(For wireless communications antenna simulation, matlab on the source code, Part IV.)

基于傅里叶变换的数字水印算法，实现了图像里的水印的嵌入和提取。Matlab代码。(Fourier transform-based digital watermarking algorithm to achieve the image in the watermark embedding and extraction. Matlab code.)

DFT进行频谱分析时的三种现象 1、混叠：对连续信号采样，要求连续信号是带限的，采样频率要足够高。Fs应满足Nyquist采样定理才不产生混叠。 采样前加低通滤波器防混叠 2、频谱泄漏：DFT对时域信号进行了截断（相当于采样信号乘了一个窗函数），时域的乘积相当于频域卷积，改变了原信号频谱。 改用其他窗函数（非矩形）改善泄漏。 3、栅栏现象：DFT 只给出了频谱在采样点上的取值，采样点间的频谱内容丢失。(DFT spectrum analysis of a three phenomena, aliasing : continuous signal sampling, requiring continuous signal is band-limited, the sampling frequency should be high enough. Fs meet the Nyquist Sampling Theorem would not have aliasing. Sampling former low-pass filter plus anti-aliasing 2, spectrum leakage : DFT right time domain signal a disconnect (equivalent to a sampling signal by a window function). time domain is equivalent to the product of frequency-domain convolution, changes in the spectrum of the original signal. Window functions to switch to other (non-rectangular) to improve leakage. 3, fenced phenomenon : DFT spectrum is given only at the sampling point value, sampling points of the spectrum as lost.)

目标跟踪仿真小程序，本程序简单易懂适合初学者学习和参考。(Small target tracking simulation program, the program simple and easy to understand for beginners learning and reference.)

说明：  matlab科学计算继续上传，一共10个章节，由浅入深，几乎包括了绝大部分的科学计算方法以及仿真。本人把部分算法做了优化，更为完善(matlab scientific computing continue to upload, a total 10 chapters, easy-to-digest, almost, including most of the scientific method of calculation and simulation. I have done a part of algorithm optimization, a more perfect)

Project Report on State space analysis of Inverted Pendulum,The Rotary Inverted Pendulum is a classic control problem that is explored often as a project in control courses due to its easily developed dynamics combined with its complexity of control design. Although, the problem can be solved using conventional control techniques like PD/PID controllers, we will use some other powerful techniques involving state space analysis. The system is composed of a pendulum attached to the end of a rotary arm controlled by a motor. The control input is in the form of voltage input to the motor. Here our objective is to keep the pendulum in upright position of unstable equilibrium.