id3-jueceshu

本文讲述的是运用matlab软件编写线性卷积和循环卷积，运行程序并得到正确结果，附上运行结果图让大家参照对比。

数字预失真的很好的算法，从原理到算法都给出比较详细的说明，对初学者有很大的帮助。(A good digital pre-distortion algorithm to the algorithm are given from the principle of a more detailed explanation, very helpful for beginners.)

说明：  提供了人工鱼群算法和RBF神经网络代码，有需要的朋友可以下载参考(AFSA offers and RBF neural network code, a friend in need can be downloaded for reference)

使用iir方法设计的数字滤波器，通过验证，功各位使用。(Designed using iir digital filter, through verification, power you use.)

MATLAB的基础应用及粗糙集理论的基础知识（PDF）(The basis of MATLAB applications and rough set theory based on knowledge (PDF))

卷积码在AWGN信道下的实现 包括simulink文件与.m文件 (Convolutional Codes in AWGN channel, including the realization of documents and Simulink. M documents)

matlab 提取SIFT特征，并完成特征点的匹配以实现复制粘贴篡改检测(Extract SIFT features of the image and match the keypoint to detect the cony-move fogery )

we address the design of economical recursive generalized comb filters (GCFs) by proposing an ef- ficient technique to quantize the multipliers in the z-transfer function employing power-of-2 (PO2) terms. GCFs are efficient anti-aliasing decimation filters with improved selectivity and quantization noise rejection performance around the so-called folding bands with respect to classical comb filters. The proposed quantization technique guarantees perfect pole–zero cancelation in the rational z-transfer function of the GCFs, thus totally avoiding instability problems. Moreover, we propose the use of a simple droop compensator for the sake of recovering the passband droop distorting the useful digital signal in the baseband. A design example is proposed with the aim of showing the application of the proposed technique, and a practical architecture of a sample third-order GCF is discussed.

电力系统工具的源文件，主要是包括了电力系统中交直流互联系统的模型，包括四机两区域(Simple and bacterial foraging optimization algorithm, mainly used for the optimization of the PID control, and can be run directly)

说明：  KSVD算法,利用LC-KSVD来进行算法的仿真，是一个不错的算法demo，希望能对大家有用。(KSVD algorithm, using lc-ksvd algorithm simulation, is a good algorithm demo, hope to be useful to you.)