10122012-Voice-recognition-LPC-VS-MFCC-with-K-NN

rossler混沌系统中，反馈增益k在有限时间内收敛到了一个合适的负常数(rossler chaotic system, the feedback gain k in a finite time convergence to a suitable negative constant)

用matlab编写的车牌识别的源程序，可以准确定位到车牌(Prepared using matlab source license plate recognition, can accurately locate the license plate)

Catastrophe theory book

DOUBLE EVAL..it is implemented in matlab

该文件中包含二次规划中涉及的matlab程序，包含拉格朗日法以及起作用集法(This file contains the quadratic programming matlab procedures involved, including the Lagrangian method and set method works)

xwch_test.m是主测试文件；biaoji.mat存放滤波器系数；xiangweicha.m用FFT计算相位差。 仿真框架为： 1.标记信号和双音信号续接作为发送信号； 2.对双音中一个频率分量的相位做偏移，再经过一个低通滤波器（引入线性相位，模拟收发不能同步测量现象）后，作为收到的信号； 3.用一个检测信号对收发信号进行相关运算； 4.画出收发信号以及相关处理后的信号。找出相关信号的那个尖点，从而推算出收发双音信号0相位点； 5. 输入0相位点位置，计算相对相位差。(xwch_test.m is the main test file biaoji.mat store filter coefficients xiangweicha.m calculated using FFT phase difference. Simulation framework: 1. Mark signals and then as a two-tone signal continued to send signals 2. On a two-tone frequency components of the phase shift to do, and then through a low pass filter (the introduction of linear phase, simulation can not simultaneously send and receive measuring the phenomenon), the as received signal 3. using a detection signal of the transceiver signal correlation operation 4. draw send and receive signals and related processed signal. Correlated signal of the cusp, which calculate the two-tone signal transceiver 0 phase point 5. Enter 0 phase point position, calculate the relative phase difference.)

simulink下封装的混合高斯的s-funcion函数。用于模型模块的搭建。(simulink package under the Gaussian mixture of s-funcion function. The structures used to model the module.)

This documentation refers specifically to Version 1.1 of SparseBayes

模拟2个独立窄带信号分别以20°，60°的方向入射到均匀线阵上，信号间互不相关，与噪声相互独立，噪声为理想高斯白噪声，阵元数为10，快拍数为200，信噪比为20dB，阵元间距分别为 tambada/6 tambada/2、tambada。(Simulate two independent narrowband signals in the direction of 20 °, 60 ° of the incident on the ULA, among signal unrelated, independent noise, the noise is ideal Gaussian white noise, the array element number 10, the number of snapshots for 200, SNR is 20dB, respectively array element spacing  tambada/6 tambada/2, tambada.)

This is Ant Based Clustering