GP-4324MATLAB

欧拉角表示法具有简便、几何意义明显等优点，同时姿态敏感器可以直接测出这些参数，能较方便地求解用这些姿态参数描述的姿态动力学方程。但采用欧拉角的姿态描述方法存在奇点问题，且需多次三角运算。而采用四元数表示方法则可以避免这些问题。(conversion between euler angle and quaternion method)

说明：  我整理的基于卡曼滤波的盲多用户检测程序，仿真结果是对应不同信噪比时的误码率(I am finishing kaman filtering based on blind multi-user detection procedures, simulation results are corresponding to different signal to noise ratio when the bit error rate)

说明：  该教程将matlab和线性代数结合起来，重点介绍矩阵的使用(This tutorial will combine matlab and linear algebra, focusing on the use of matrices)

pca orl 人脸数据库 识别人脸 带精确度

同步变化的学习因子的粒子群算法，学习因子不为固定的常数(LnCPSO)

此m文件为脚本文件，在命令窗口输入命令：midamble，即可执行！ 单元数组--user_m，存储了K个用户的midamble码，user_m{1}对应用户1，以此类推。(This m file for the script file, enter the command in the command window: midamble, which can be executed! Cell array- user_m, stored K users of the midamble code, user_m (1) corresponds to user 1, and so on.)

　Buck-Boost转换器转换周期轨道从混乱的状态,本文提出一种　　混沌控制方法通过改善电感电流和输出电压之间的关系。通过调整　　耦合强度,这种方法可以控制混沌周期2 Buck-Boost转换器,period-4,period-8轨道　　period-9轨道和周期3,时间6,不确定不稳定周期轨道(着)。(To transform the Buck-Boost converter the chaotic state to the periodic orbits, this paper proposes a chaotic control method by improving the correlation between the inductor current and the output voltage. By adjusting the coupling strength, this method can control the chaotic Buck-Boost converter to the period-2, period-4, period-8 orbits and the period-3, period-6, period-9 orbits, without determining the unstable periodic orbits (UPOs) in advance.)

用C语言编写MATLAB 函数, 主要用于DSP芯片上， 也可用于参考将C语言转换为汇编(Use the programming language C to write MATLAB function, histeq )

i have attached some matlab file

研究表明，构成K一L变换矩阵的向量也就是ToePhtz矩阵的特征向量。与此同时，离散 余弦变换矩阵逼近于ToePutz矩阵的特征向量矩阵，所以离散余弦变换矩阵与自然图像的 K一L变换矩阵十分相似。经过离散余弦变换后的变换系数块的协方差矩阵Cy非常接近对角 阵，即除了对角线元素以外，其它很多元素都近似为0，并且在左上角集中了主要能量。这 反映了自然图像大部分区域变化不大，亮度突变只占少数，即图像能量以低频成分为主的特 性。通过变换后的量化，舍弃对视觉效果影响较小的次要信息，可达到进一步的压缩效果。 虽然从去相关性能的意义上讲，DCT是一种次于K一L变换的准最佳变换，但是从算法实现的角度来看，DCT则远远优于K一L变换。首先，当图像的分块大小确定后，DCT的变换矩阵也就随之确定了，不随输入信号的统计特性变化而变化 其次，二维DCT能够分解成两次一维DCT，有利于硬件实现。 (Studies have shown that constitute a K L transformation matrix vector is ToePhtz eigenvector of the matrix. At the same time, discrete The cosine transform matrix approximation in ToePutz matrix eigenvector matrix, so the discrete cosine transform matrix and natural images Is very similar to a K L transformation matrix. After discrete cosine transform, the transform coefficient block of Cy is very close to the diagonal of covariance matrix Matrix, namely except diagonal elements, many other elements are approximate to 0, and focused the main energy in the upper left corner. this Reflects the natural images most area changed little, brightness mutations accounted for only a few, the energy is given priority to with low frequency components of image Sex. Through quantitative after transformation, abandoning smaller effect on the visual performance of secondary information, can achieve further compression effect. Although from related to the performance of the sense, DCT is a kind o)