Copy-of-projj

reconocimiento de voz david robert s

报告第二部分给出了均衡器结构以及迫零均衡器和最小均方误差均衡器理论推导，第三部分 给出了均衡器的 Matlab 仿真；第四部分给出了两种均衡器的仿真结果及对比；附录给出了两种 均衡器的 Matlab 程序，总的程序，以及托普利兹矩阵与卷积作比较和自相关的计算。(The second part of the report gives the theoretical derivation of the equalizer structure and the zero-forcing equalizer and the minimum mean-square error equalizer. The third part gives the Matlab simulation of the equalizer. The fourth part gives the simulation results of the two equalizers And contrast; Appendix gives two kinds of equalizer Matlab program, the total program, as well as the comparison and autocorrelation of Toledith matrix and convolution calculations.)

双目视觉三维重建程序，输入左右相机匹配点对矩阵，自动计算投影矩阵，并输出射影空间下的三维点坐标(Binocular vision three-dimensional reconstruction program, enter the matching points on the matrix around the camera to automatically calculate the projection matrix, and output under the three-dimensional projective space point coordinates)

4PSK的MATLAB源码程序,其中有相应的函数,是使用蒙特卡罗方法实现的.(The MATLAB source 4PSK procedures, of which the corresponding function, is achieved using the Monte Carlo method.)

说明：  用于人工智能分类算法仿真的数据集 UCI数据集 已经过集成(Simulation of artificial intelligence classification algorithm for data sets UCI data sets have been integrated)

批量处理灰度图像，并能够识别图像质量中心进行截圆处理，同时生成灰度直方图以及各个点的坐标文件(Batch processing grayscale images, the image quality and the ability to identify the center circle cut deal, while generating histogram and the coordinates of each point file)

说明：  matlab简单例程，可以熟悉矩阵的建立、提取、逻辑循环等功能(matlab simple routine, familiar with the matrix can be set up, extraction, logic cycle and other functions)

混合编程时，M文件中调用C语言函数，精通matlab编程一书的例程，希望有帮助。(mixed programming, the paper called M C language function, proficient Matlab programming routines in a book. hope it helps.)

matlab中对GUI的操作，熟悉在GUI中控件的操作(matlab in the operation of the GUI, and familiar with the operation of the control in the GUI)

The sparsity of signals and images in a certain trans-form domain or dictionary has been exploited in many applications in signal and image processing. Analytical sparsifying transforms such as Wavelets and DCT have been widely used in compression standards. Recently, synthesis sparsifying dictionaries that are di-rectly adapted to the data have become popular especially in appli-cations such as image denoising, inpainting, and medical image re-construction.