Mandelbrot

In frequency-domain blind source separation (BSS) for speech with independent component analysis (ICA), a practical parametric Pearson distribution system is used to model the distribution of frequency-domain source signals.(In frequency-domain blind source separation (BSS) for speech with independent component analysis (ICA), a practical parametric Pearson distribution system is used to model the distribution of frequency-domain source signals.)

The basic steps of the connected-component text extraction algorithm are given below, and diagrammed in Figure 10. The details are discussed in the following sections. 1. Convert the input image to YUV color space. The luminance(Y) value is used for further processing. The output is a gray image. 2. Convert the gray image to an edge image. 3. Compute the horizontal and vertical projection profiles of candidate text regions using a histogram with an appropriate threshold value. 4. Use geometric properties of text such as width to height ratio of characters to eliminate possible non-text regions. 5. Binarize the edge image enhancing only the text regions against a plain black background. 6. Create the Gap Image (as explained in the next section) using the gap-filling process and use this as a reference to further eliminate non-text regions the output.

系统辨识与自适应控制程序 matlab 仿真 能达到很好的效果(System identification and adaptive control program matlab simulation can achieve good results)

TC环境下C语言实现的类似于matlab的数字信号和数字系统分析。使用图形界面，具有坐标显示。可以有z变换后的系统函数直接分析系统的幅频和相频响应(TC C language environment similar to matlab digital signal and digital systems analysis. Use graphical interface, with coordinates display. Z-transform can be directly after the system function of the amplitude-frequency analysis system and phase-frequency response)

深度图生成，基于立体匹配获取的深度图质量较好(Depth map, depth map based on good quality stereo matching Being)

In a multiple transmit antenna, single antenna per receiver downlink channel with limited channel state feedback, we consider the following question: given a constraint on the total system-wide feedback load, is it referable to get low-rate/coarse channel feedback from a large number of receivers or high-rate/high-quality feedback from a smaller number of receivers? Acquiring feedback from many receivers allows multi-user diversity to be exploited, while high-rate feedback allows for very precise selection of beamforming directions. We show that there is a strong preference for obtaining high-quality feedback, and that obtaining near-perfect channel information from as many receivers as possible provides a significantly larger sum rate than collecting a few feedback bits from a large number of users.

mathlab code for tdoa demo

SOME SIMULINK OF ASYNCHRONE MADA 11AQDGQQDTT

MIMO channel capacity for rayleigh fading system

matlab30个小程序matlab30个小程序(matlab30 small programs small program matlab30)