matlab-kalman-filter

this file show the simulation of induction speed

orthogonal frequency division multiplexing

产生QPSK信号，根据仿真的数据估计差错概率(Produce QPSK signal and estimate the data according to the error probability)

采用二次型性能指标学习算法的PID控制程序，欢迎下载。(The use of quadratic performance index of the learning algorithm PID control procedures, please download.)

设定噪声为高斯白噪声，对2ASK、2FSK、2PSK、2DPSK等各种调制方式及相应的主要解调方式下（分相干与非相干）的误码率进行统计，并与理论值进行比较，以图形方式表示误码率与信噪比间的关系。(Set the noise is Gaussian white noise, right 2ASK, 2FSK, 2PSK, 2DPSK a variety of modulation and corresponding demodulation mode, the main (sub-coherent and non-coherent) and bit error rate statistics, and compared with the theoretical value , a graphical representation of the bit error rate and SNR relationships.)

说明：  基于遗传算法的简单一元函数和多元单峰函数的优化(基于Sheffield的遗传算法工具箱)(A simple genetic algorithm and multi-functions of one variable optimization of a single peak function)

线性最小均方误差估计，估计恢复出的信号星座图(The linear minimum mean square error estimation，Estimation of LMMSE signal constellation restoration)

分别利用一维logistic、三维lorenz混沌映射实现任意尺寸彩色图像加密与解密（像素值及其位置都发生了改变）。密钥为混沌序列初始值。（内有详细说明）(Respectively, using one-dimensional logistic, three-dimensional lorenz chaotic mapping to achieve any size color image encryption and decryption (pixel values ​ ​ and their positions are changed). Key to the initial value of the chaotic sequence. (With detailed instructions))

说明：  该课题为基于MATLAB的bp神经网络的交通标志识别系统，可以识别禁令标志，警示标志，指示标志三种标志，带GUI界面，流程为，输入测试图，训练，定位，分割，识别。可自动识别是三种中的哪一种。定位是采用颜色的方法，分割是几何位置分割，识别bp神经网络。注释详细。(This project is a traffic sign recognition system based on BP neural network of MATLAB. It can recognize three kinds of signs: prohibition sign, warning sign and indication sign. It has GUI interface. The flow is: input test chart, training, positioning, segmentation and recognition. Which of the three can be automatically identified. The location is based on the color method, and the segmentation is based on the geometric position segmentation to recognize the BP neural network. Note details.)

this matlab code to help you finding the Color Image Threshold