水声信道仿真 channels

分别设计理想低通滤波器、巴特沃思滤波器、指数滤波器、梯形低通滤波器,并对含高斯噪声的图像进行低通滤波，截止频率自选，观察不同的截止频率,不同的滤波器的滤波效果。(Were designed for the ideal low pass filter, Butterworth filter, exponential filter, ladder low-pass filter, and Gaussian noise images with low-pass filter cutoff frequency chosen to observe the different cut-off frequency, different filter filtering device.)

1. BPSK modulation of data which ever you input (default data is “MANIPAL REDDY”). 2. MANIPAL REDDY is changed into ASCII Format and into two-bit format for BPSK Modulation. 3. Chaos is used for spreading the binary bit sequence. 4. Uniformly distributed Noise is added to Spread signal. 5. After reception Chaotic Chip sequence is used to recover message . 6. Filter is used for removing spikes and noise. 7. Note the filter is used is just for showing a little realisitic picture. 8. Appropriate filter should be used. 9. The original data in binary and recovered data in binary format are compared

信号与系统是通信和电子信息类专业的核心基础课，其中的概念和分析方法广泛应用于通信、自动控制、信号与信息处理、电路与系统等领域。 (Signal and system is the communication and electronic information specialty core courses, one of the concepts and methods of analysis are widely used in communication, automatic control, signal and information processing, circuit and system etc..)

说明：  高校图象处理,里面的图画可以自己去找一张然后放到程序指定路径即可(college image processing, the picture inside themselves and they can then put a process can be designated trails)

解决离散傅里叶变换的能量泄露问题，使得傅里叶变换的结果更加的准确。(Solving the Energy Leakage Problem of Discrete Fourier Transform)

说明：  RLS算法的matlab实现,可用于各种自适应滤波的仿真(rls )

matlab课程教材上的所有代码，罗小巧老师的matlab(All course materials on the matlab code matlab Luo small teacher)

svm is a discriminative classifier

利用matlab自带的BP神经网络工具箱对duffing混沌背景模型进行相空间重构与预测，程序中已经给出duffing函数，主函数中也给出了主要注释，方便大家学习交流。(BP' s own use matlab neural network toolbox for duffing chaotic background model and prediction of phase space reconstruction, the program has been given duffing function, the main function also gives the main note, we facilitate learning exchanges.)

On Cluster Validity for the Fuzzy c-Means