Speech-recognition-in-MATLAB-

Kernel density based probability estimation and filtering for a signalProa

仿真对象如下： 其中， v( k )为服从N (0,1) 分布的白噪声。输入信号u ( k) 采用M 序列，幅度为 1。M 序列由 9 级移位寄存器产生，x(i)=x(i-4)⊕x(i-9)。 选择如下辨识模型： 加权阵取Λ = I。 衰减因子β = 0.98，数据长度 L = 402。 辨识结果与理论值比较，基本相同。辨识结果可信 (he simulation object is as follows: among them, v (k) to obey N (0, 1) distribution of white noise. The input signal u (k) using M sequence, amplitude is 1. M sequence by 9 level shift register generation, x (I) = x (I- 4) ⊕ x (I- 9). Choose the identification model: weighted array take Λ = I. Attenuation factor β = 0.98, the data length L = 402. Identify the theoretical calculation and comparison, basically the same. Identification results are reliable)

some dataset for weka some dataset for weka

小波分析在语音特征参数提取方面的应用,很实用，经测试！(Wavelet analysis in terms of the voice feature extraction!)

Testing functions with double-byte names.

通过虚拟阵元进行DOA估计，包括面积、周长、矩形度、伸长度，合成孔径雷达（SAR)目标成像仿真，matlab编写的元胞自动机，数学方法是部分子空间法。(Conducted through virtual array DOA estimation, Including the area, perimeter, rectangular, elongation, Synthetic Aperture Radar (SAR) imaging simulation target, matlab prepared cellular automata, Mathematics is part of the subspace.)

For computing the BER for BPSK modulation in a Rayleigh fading channel with selection diversity.

it generates a runtime error if its this value is not a Number object.

说明：  Adaboost是一种迭代算法，其核心思想是针对同一个训练集训练不同的分类器(弱分类器)，然后把这些弱分类器集合起来，构成一个更强的最终分类器（强分类器）。(AdaBoost is an iterative algorithm. The core idea of AdaBoost is to train different classifiers (weak classifiers) for the same training set, and then combine these weak classifiers to form a stronger final classifier (strong classifier).)

此函数为matlab函数，可以用来绘制出任意函数的包迹线。(Finds the envelope of an arbitrary function)