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一篇经典论文的代码，“Saliency,Scale,image description”，用于寻找视觉显著性的区域，matlab代码(A classic papers of the code, " Saliency, Scale, image description" , for the visual search of the area significantly, matlab code)

Matlab常用信号产生函数演示实例：编写一个M文件，依次产生均匀分布的随机序列、高斯白噪声随机序列、方波信号序列、三角波信号序列、正弦波信号序列，以及信噪比SNR为10dB的加性高斯白噪声正弦信号。(Matlab commonly used signal generating function demo examples: write a M file, in turn generating uniformly distributed random sequences, Gauss white noise sequence, square wave signal, triangle wave signal sequence, sine wave signal sequence, as well as for the 10dB than the SNR signal-to-noise additive Gauss white noise sine signal.)

The video motion is estimated based on the diamond search algorithm

模式识别中的模糊聚类，采用隐马尔科夫链，考虑了先验概率，进行图像识别。(Pattern recognition, fuzzy clustering, using hidden Markov chain, taking into account a priori probability for image recognition.)

编译原理的实验，整个讲解过程及编码,对新手很有帮助啊(Compilation Principle of the experiment, the whole process and explain the codes, very helpful to the novice ah)

这是在数值计算时经常用的样条插值的程序，能够在在MATLAB环境下直接运用。(This is the numerical calculation frequently used spline interpolation procedures in the MATLAB environment direct use.)

it is code for temporal feature extraction

IEEE papers for Dilutiion of Precision

说明：  两种不同的假设： H1 ： 0 xn A fn wn ( ) cos(2 ) ( ) = ++ π θ n=1,2,…,N，f0 为规一化频率 H0 ： xn wn () () = n=1,2,…,N 其中 w[n]是均值为 0，方差为 2 σ n 的高斯白噪声，A 已知，样本间相互 独立，信号与噪声相互独立; 相位θ 是随机变量，它服从均匀分布 1 0 2 ( ) 20 p θ π θ π ?? ≤ ≤ = ??? 其它 1）改变输入信噪比（改变 A 或噪声方差均可），给定虚警概率，画出 输入信噪比与检测概率之间的理论曲线。(注意：理论检测曲线与样本 数有关) 2）改变样本数，用 Monte-Carlo 实验方法得出 PF＝0.001 时输入信噪比 与检测概率之间关系曲线（至少三条），并得出结论。 3）改变 M-C 实验次数，样本数不变，用 Monte-Carlo 实验方法得出 PF ＝0.001 时输入信噪比与检测概率之间关系曲线（至少三条），并得出 结论(Draw the theoretical curve between input SNR and detection probability)

用Matlab实现RLS算法 画出原始信号和处理后的信号进行对比 (RLS algorithm using Matlab to draw to achieve the original signal and processed signal to compare)