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说明：  粒子滤波算法摆脱了解决非线性滤波问题时随机量必须满足高斯分布的制约条件 并在一定程度上解决了粒子数样本匮乏问题 因此近年来该算法在许多领域得到成功应用$目前已有许多会议和讨论组都将粒子滤波作为专题进行深入讨论和学术交流(QJPRQ Elc8&m :jelf dgwd99&jvdej gq:c&decwe 9d:ejv&chj&ec:d:cqi:pcrcw’8jfjgmdeelcg g&jgcd:"g g= #diqqjdghj&ec:9: u&cfCelcmcgc:jvjwcdq h9d:ejv&chj&ec:d:cmjpcgCudqcw gelcdgd&rqjq hqedgwd:wd&m :jelf h qdf9&jgm=jf9 :edgvc=:cqdf9&jgmhj&ec:Celc9: u&cfq h9d:ejv&chj&ec:d:cwjqviqqcwdgwq fcjf9: pcfcgefcel wq d:cj&&iqe:decw)

用matlab结合窗函数法、等波纹设计法实现FIR滤波器(Combined with matlab window function method, such as corrugated FIR filter design method)

在小波域中，以图像作为水印信息，嵌入以声音为载体信号的源程序。(n wavelet domain to image as a watermark, embedded with sound as the carrier signal source program. )

极值分布的参数的极大似然估计，并绘图比较(Extreme value distribution parameters of maximum likelihood estimation, and drawing comparison)

Histogram of letters and pair of letters from a text file.

mathlab基本计算指令，包括矩阵，微分求导等运算(fff)

AUTOENHANCE Automatically adjusts/enhances the image(brightness, color and contrast) to "optimum" levels.

说明：  一维信号BP重构算法，先生成稀疏度为K的稀疏矩阵，再加入高斯白噪声进行算法重构以及质量衡量。(BP signal reconstruction algorithm for one dimensional, Mr. into sparse matrix sparsity of K, then the Gauss white noise and measure the quality of reconstruction algorithm.)

DCT 3D function for signal

Raghuraj 与 Lakshminarayanan提出了基于特征值内相互关系建立预测模型,用于识别的模式识别方法——多变量预测识别模型（Variable Predictive Mode Based Class Discriminate, VPMCD）,并应用于生物学的模式识别中。VPMCD利用参数估计来建立预测模型，极大地减少了计算量，缩短了模型的训练时间。vpmcd5_revise为主函数，sec2_5_revise为训练函数(Variable Predictive Mode Based Class Discriminate, VPMCD)