mm1coba

小波变换获得细节和逼近子图，再求子图能量 用L1范数来求(wavelet transform energy)

生成数字信号处理课程常用信号：冲激、阶跃、斜坡、正弦、复指数和指数信号，幅度长度时延频率相位可控。(Signal generation, capable of generating pulse, step, ramp, sine, complex sine and exponent signals.)

说明：  fcm实现简单的数值分类，只要你重新定义数据矩阵，就可以直接进行分类。(FCM implements simple numerical classification, which can be directly classified as long as you redefine the data matrix.)

《工程线性代数》源代码，包含书中每个例子代码，经过调试，版本matlab7.0(" Linear Algebra Project," the source code, including examples of code for each book, after debugging, version matlab7.0)

用窗函数法设计FIR数字滤波器。包括：1.矩形窗2.三角窗3.汉宁窗4.海明窗5.布拉克曼窗6.凯泽窗等(FIR digital filter design with a window function method. Including: a rectangular window. Triangular window. Hanning Hamming window, Blackman window and Kaiser window)

this is the sudoku game by using matlab

运用差分进化算法（DE）优化分数阶pid控制器(Use of differential evolution algorithm (DE) optimization of fractional order pid controller)

将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序(Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality reduction. To recover a signal from its compressive measurements, standard CS algorithms seek the sparsest signal in some discrete basis or frame that agrees with the measurements. A great many applications feature smooth or modulated signals that are frequency sparse and can be modeled as a superposition of a small number of sinusoids. Unfortunately, such signals are only sparse in the discrete Fourier transform (DFT) domain when the sinusoid frequencies live precisely at the center of the DFT bins. When this is not the case, CS recovery performance degrades significantly. In this paper, we introduce a suite of spectral CS (SCS) recovery algorithms for arbitrary frequency sparse signals. The key ingredients are an over-sampled DFT frame, a signal model that inhibits closely spaced sinusoids, and classical sinusoid parameter e)

Simulation for wireless sensor relaying network using DF model

Book - Introduction to pattern recognition : a MATLAB approach - Sergios Theodoridis.