Ringdown-Tools_030902

L3_1.m: 純量量化器的設計(程式) L3_2.m: 量化造成的假輪廓(程式) L3_3.m: 向量量化器之碼簿的產生(程式) L3_4.m: 利用LBG訓練三個不同大小與維度的碼簿並分別進行VQ(程式) gau.m: ML量化器設計中分母的計算式(函式) gau1.m: ML量化器設計中分子的計算式(函式) LBG.m: LBG訓練法(函式) quantize.m:高斯機率密度函數的非均勻量化(函式) VQ.m: 向量量化(函式) L3_2.bmp: 影像檔 lena.mat: Matlab的矩陣變數檔 (L3_1.m: scalar quantizer design (the program) L3_2.m: quantitative result of the false contour (the program) L3_3.m: Vector quantizer code book of the generation (the program) L3_4.m: training in the use of LBG three different size and dimension of the code book and separate VQ (program) gau.m: ML quantizer design in the denominator of the calculation formula (function) gau1.m: ML quantizer design in the calculation of molecule-type ( function) LBG.m: LBG training method (function) quantize.m: Gaussian probability density function of the non-uniform quantization (function) VQ.m: vector quantization (function) L3_2.bmp: image file lena.mat: Matlab matrix variable file)

经验模态分解 亲测好用，可以带入自己的数据(Empirical modal decomposition is easy to use and can bring in its own data.)

功能为neighborhood components analysis，a quick matlab implementation of NCA (see Goldberger et al, NIPS04). (err)

蔡氏混沌电路的仿真,混沌同步中常用同步方法的仿真，基于蔡氏混沌电路(cai chaos control)

已知两点经纬度，计算两点之间距离。 利用大地坐标！(The known longitude and latitude calculate the distance )

介绍了匹配滤波器 LFM信号的匹配滤波器,用于信号距离探测(the matched filter for signal detection distance)

该文件为功率谱估计的一个子程序，对广大读者很有帮助，现在拿出来和大家一起分享下(The file is a subroutine power spectrum estimation of readers helpful, and now share with everyone out under)

说明：  使用自编函数基于奇异值分解总体最小二乘法（svd-tls）实现AR模型谱估计 (The use of self-functions in general based on singular value decomposition least square method (svd-tls) to achieve AR model spectrum estimation)

cdbn.卷积深度信念网络用于声音识别。此代码为老外写的matlab代码(Cdbn. convolutional depth belief network for identification of sound. This code for a foreigner to write matlab code Cdbn. convolutional depth belief network for identification of sound. This code for a foreigner to write matlab code )

Estimated number of Pi ( Method 1) how do we estimate Pi by simulation? In the simulation, you keep throwing darts at random onto the dartboard. All of the darts fall within the square, but not all of them fall within the circle. Here s the key. If you throw darts completely at random, this experiment estimate the ratio of the area of the circle to the area of the square, by counting the number of darts in each. Our study of the geometry tells us this ratio is Pi/4. So, now we can estimate Pi as