8-nodes

K -Plets Graph Theory based. (K-Plets Graph Theory based. )

说明：  利用MATLAB语言编写的直流电动机瞬态运行特性分析的程序(The use of MATLAB language to run the DC motor characteristics of the transient process)

北京工业大学MATLAB课件的ppt和word文档的总结概括(Beijing University of MATLAB Courseware ppt and word summed up the document)

for removal used to remove the fog and get clear image

线性非时变系统的卷积的demo，有助于对卷积的理解。欢迎大家分享之(As one would learn in a basic signal processing/controls/dynamical systems class, the multiplication by an LTI transfer function F(s) in the frequency domain is the same operation as convolution with f(t) in the time domaininformation hiding that is known as self-embedding. In essence, the process embeds a copy of the media into itself, of course it goes without saying that the copy has to be encrypted before the embedding takes place. The program is written purely in MATLAB with some scripts in PHP and HTML. )

ACF中包含两个m文件，一个是自协方差函数（可单独使用）。另一个是自相关函数计算，其调用autocov函数。(ACF contains two m files, one is self-covariance function (which can be used alone). The other is calculated from the correlation function, which calls autocov function.)

Huffman编码算法是一种基于信源符号概率的变长码编码算法 (Huffman coding algorithm is based on the probability of source symbol variable-length coding algorithm)

用MATLAB实现的DSP函数，包括FFT、ChripZ、DCT、DELTA、Hilbert变换(用MATLAB实现的DSP ??数 ???? ?FFT ??ChripZ ??DCT ??DELTA ??Hilbert ??换)

MATLAB implementation of SPIHT (without Arithmatic coding stage). ％ Performance evaluation : this toolbox VS. SPIHT ％ Test image: lena512.raw ％ bpp SPIHT(dB) This code(dB) ％ 0.1000 29.8107 29.3202 ％ 0.2000 32.7202 32.2514 ％ 0.3000 34.5479 34.0331 ％ 0.4000 35.8422 35.4857 ％ 0.5000 36.8623 36.5939 ％ 0.6000 37.6650 37.3759 ％ 0.7000 38.2581 38.0491 ％ 0.8000 38.9390 38.7058 ％ 0.9000 39.5218 39.3437 (MATLAB implementation of SPIHT (without A rithmatic coding stage). Performance evalua% tion : this toolbox VS. SPIHT%% Test image : lena512.raw%% bpp SPIHT (dB) This code (dB)% 0. 1000 29.8107 32.7202 0.2000 29.3202% 32.2514% 0.3000 0.4000 34.5479 34.0331% 35.8422 35.485 7% 0.5000 0.6000 36.8623 36.5939% 37.6650 37.3 759% 38.0491% 0.7000 0.8000 38.2581 38.9390 38 .7058 0.9000 39.5218 39.3437%)

a kind of svm toolbox