完美的常用数字信号调制调试工具

自适应系统源程序，比较简单，希望能对大家有所帮助(Adaptive system source code is relatively simple, we hope to help)

Convex optimizations using cvx tool box

modele of floutp you can utise thise simulion ofn to gett the correct value

认知无线电的能量检测算法，是很珍贵的材料，老板推荐的哦(Energy detection algorithm for cognitive radio)

基于svm的一维信号的回归预测，精确度优于传统的神经网络方法(The one-dimensional signal based svm regression prediction accuracy is better than traditional neural network method)

仿真图是速度、距离、幅度三维图像，包括压缩比、运行时间和计算复原图像的峰值信噪比,自己编的5种调制信号，用于图像处理的独立分量分析，本程序的性能已经超过其他算法，包括回归分析和概率统计。

改程序实现了mimo的中断容量在仿真区域中的三维分布情况(Procedures to achieve the outage capacity of mimo at the three-dimensional simulation of the regional distribution of)

对于离焦图像进行自动对焦的图像判定，通过对一些列的图像，从离焦到对焦再到离焦进行图像分析从而获得对焦图像的图片。(For the defocus image autofocus image determination, through a series of images into focus and then from defocus defocused image analysis to obtain a focused image of the picture.)

Traditional single particle reconstruction methods use either the Fourier or the delta function basis to represent the particle density map. We propose a more flexible algorithm that adaptively chooses the basis based on the data. Because the basis adapts to the data, the reconstruction resolution and signal-to-noise ratio (SNR) is improved compared to a reconstruction with a fixed basis. Moreover, the algorithm automatically masks the particle, thereby separating it from the background. This eliminates the need for ad-hoc filtering or masking in the refinement loop. The algorithm is formulated in a Bayesian maximum-a-posteriori framework and uses an efficient optimization algorithm for the maximization. Evaluations using simulated and actual cryogenic electron microscopy data show resolution and SNR improvements as well as the effective masking of particle from background

实现了图像的加水印，去噪，加噪声等功能，BP神经网络用于函数拟合与模式识别，LDPC码的完整的编译码。( Realize image watermarking, de-noising, plus noise and other functions, BP neural network function fitting and pattern recognition, Complete codec LDPC code.)