Matlab2dGaussinafilling

利用PSO算法设计传感器的动态补偿器，使补偿之后的传感器的动态性能指标得到提高。(PSO algorithm design using dynamic compensation of sensor devices for the compensation of the sensor after the dynamic performance is improved.)

经典gatbx遗传算法工具箱，包含说明文档(failed to translate)

matlab实现三维CT图像的分割，阈值分割法来实现(Three-dimensional CT images matlab segmentation, threshold segmentation method to achieve)

通过计算机MATLAB仿真分析和研究了维纳滤波器的阶数、信号的噪声方差、随机信号的采样点数、经过维纳滤波的均方误差之间的关系(MATLAB simulation by computer analysis and research of Wiener filter order, the signal of the noise variance, random signal sampling points, after Wiener filter mean square error of the relationship between)

ICA算法的详细介绍，包括算法的主要步骤。最后还附有一个实例，有相应的程序，方便使用。(A detailed description of the ICA algorithm, including the main steps of the algorithm. Finally, accompanied by an instance of the corresponding program, easy to use.)

连续时间切换线性随机系统稳定最小驻留时间搜寻程序(Continuous-time switched linear stochastic system is stable minimum dwell time of the search procedures)

high-end mathematical algorithm matlab source

不考虑不平衡磁拉力（UMP），转子系统在自身的质量、阻尼、弹簧等作用下，轴心轨迹求解方法(unbalanced magnetic pull is not considerated and rotor center orbit is gotten)

Huffman source code for matlab.

研究表明超高斯分布更加贴近语音信号的实际分布，然而语音信号很难用单一的概率密度 函数准确描述，针对这一情况，提出了一种用超高斯混合模型对语音信号幅度谱建模的新方法，并推导了 基于此模型的幅度谱最小均方误差估的估计式。仿真结果表明：与传统的短时谱估计算法相比，该算法不 仅能够进一步提高增强语音的信噪比，而且可以有效减小增强语音的失真度，提高增强语音的主观感知 质量。 (Recent research indicates that the speech spectral amplitude distributions could be fairly described with super-Gaussian probability density function. However, the complexity of speech signal determines that the distribution statistics ofspeech signal could not be well described by single simple function. Thus a super-Gaussian mixture model for speech spectral amplitude is proposed, and with this model, a minimum mean-square error (MMSE) estimator for speech signals spectral amplitude is derived. The simulation results show that this algorithm based on Gaussian and super-Gaussian speech model could achieve better noise suppression and lower speech distortion as compared with the conventional short-time spectral amplitude estimation algorithm. )