电动出租车的充电负荷计算

对电力系统中传统机组进行机组组合优化计算(The unit commitment optimization of the traditional power unit is calculated)

Gold sequence generator

matlab经典程序 包含多个程序 值得借鉴(matlab classic several matlab classic codes)

该程序是MATLAB源程序，可以用来对图像进行延拓，方便进行EMD分解。(MATLAB source code of the procedure can be used to image extension, facilitate the EMD decomposition.)

Canys edge detection algorith implemented.

说明：  学习信号与系统时的一些matlab例子,以及一些马达控制的PID算法.(Learning signals and systems to some of the matlab examples, and some motor control PID algorithm.)

DTMF(双音多频)是用两个特定的单音频组合信号来代表数字信号的一种编码技术。两个单音的频率不同，代表的数字或实现的功能也不同。可采用8种频率代表电话机上的16个按键，10个数字键0~9和6个功能键*、#、A、B、C、D。具体的频率组合见参考书。要求： (1) 根据键盘输入的符号，利用MATLAB产生对应的DTMF信号；(2) 分别利用FFT算法和Goertzel算法计算该DTMF信号的频谱并画出频谱图；(3) 根据频谱图确定DTMF信号所代表的符号是否和输入的符号一致。 (DTMF (Dual Tone Multi-Frequency) is a single with two specific combination of audio signals to represent a kind of digital signal coding techniques. Two monosyllabic different frequency, on behalf of the numbers, or the realization of the functions are also different. Eight kinds of frequency of use on behalf of telephone on the 16 keys, 10 numeric keys 0 ~ 9 and 6 function keys*,#, A, B, C, D. The frequency of specific composition of reference books. Requirements: (1) According to the keyboard input of symbols, the use of MATLAB have a corresponding DTMF signal (2), respectively, using FFT algorithm and the Goertzel algorithm DTMF signal spectrum and frequency spectrum draw (3) According to DTMF signal frequency spectrum to determine represented by symbols and input symbols unanimously.)

生物地理算法优化多层感知网络进行特征分类和识别，精度高达97 (Bio geographic algorithm to optimize multi layer perceptron network for feature classification and recognition, the accuracy of up to 97 )

不错的GM_EM代码。用于聚类分析等方面。( GM_EM- fit a Gaussian mixture model to N points located in n-dimensional space. Note: This function requires the Statistical Toolbox and, if you wish to plot (for k = 2), the function error_ellipse Elementary usage: GM_EM(X,k)- fit a GMM to X, where X is N x n and k is the number of clusters. Algorithm follows steps outlined in Bishop (2009) Pattern Recognition and Machine Learning , Chapter 9. Additional inputs: bn_noise- allow for uniform background noise term ( T or F , default T ). If T , relevant classification uses the (k+1)th cluster reps- number of repetitions with different initial conditions (default = 10). Note: only the best fit (in a likelihood sense) is returned. max_iters- maximum iteration number for EM algorithm (default = 100) tol- tolerance value (default = 0.01) Outputs idx- classification/labelling of data in X mu- GM centres)

说明：  简单的GA算法,适合想要学习遗传算法的初学者好好看看(a simple example of GA)