Boost_converter

这是MATLAB进行信道建模的例子，有兴趣的同志可以下来看看，总有帮助的(This is the MATLAB modeling channel to the example of the comrades who are interested can look at it, there is always help)

Today, there is almost no area of technical endeavor that is not impacted in some way by digital image processing.We can cover only a few of these applications in the context and space of the current discussion. However, limited as it is, the material presented in this section will leave no doubt in the reader’s mind regarding the breadth and importance of digital image processing.We show in this section numerous areas of application, each of which routinely utilizes the digital image processing techniques developed in the following chapters. Many of the images shown in this section are used later in one or more of the examples given in the book. All images shown are digital.

gabor for fingerprint matlab

BOC(2,1)的编码，BOC(2,1)的功率谱密度，可以完美运行，对做BOC编码的人很有用途(BOC (2,1) code, BOC (2,1) power spectral density, can run perfectly on the very people who make use of BOC coding)

simulink下茶油发电机模型 采用PID自适应控制，适合船舶电力推进发电机( Diesel generator)

数字通信系统中，基于MATLAB的几种常见信号的仿真(Digital communication system, based on several common signal MATLAB simulation)

改程序能够实现加窗插值FFT算法的matlab仿真，已经得到实验验证，注解清晰详细，代码可读性强.以512点为例进行仿真计算，对与其他点数，如256或是1024可以通过简单修改即可(Reform process to achieve the windowed interpolation FFT algorithm matlab simulation, experimental verification has been, clear and detailed annotations, code readability. 512 points as an example to the simulation of other points, such as 256 or 1024 can be simple modifications)

一个讲述MATLAB偏微分方程工具箱的 PDF 文件(A MATLAB PDE toolbox about PDF files)

从已经出现故障的信号中，提取能够反映该信号故障特征的值，以后就能根据数值直接判断别的信号有没有出现该故障，更加直观(Signals the fault has appeared in the fault feature extraction and can reflect the value of signal, after can according to numerical directly to judge the other signals have appeared the fault, more intuitive)

This paper addresses the problem of segmenting an image into regions. We defi ne a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an effi cient segmentation algorithm based on this predicate, and show that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties. We apply the al-gorithm to image segmentation using two diff erent kinds of local neighborhoods in constructing the graph, and illustrate the results with both real and synthetic images. The algorithm runs in time nearly linear in the number of graph edges and is also fast in practice. An important characteristic of the method is its ability to preserve detail in low-variability image regions while ignoring detail in high-variability regions.