UC3854

在视图类CDemoView中映射“拉普拉斯锐化”事件的处理函数:OnLaplacienSharp()，以下是CDemoView:: :OnLaplacienSharp()函数的代码实现。(In the view class CDemoView in the mapping " Laplacian sharpening" event handler: OnLaplacienSharp (), following CDemoView::: OnLaplacienSharp () function code.)

This sliceomatic file is coded based on the slice fucntion in MATLAB It can be used to view the shape of various 3D strucntures,whoes cross sections can also be shown.

说明：  《精通Matlab与C/C++混合程序设计》（ 第一章）("proficient Matlab and C/C mixed Program Design" (first chapter))

Speed Control of a DC Motor Using BJT H-Bridge This demonstration illustrates simulation of a H bridge used to generated a chopped voltage and control speed of a DC motor, in open loop, in both directions

在matalab开发环境下的实现时域信号多尺度的分析，可用于信号的特征抽取和故障诊断(Multi-scale analysis of time-domain signal achieved in matalab development environment can be used for feature extraction and fault diagnosis signal)

硕士论文，基于机器视觉苹果检测算法的研究。主要内容包括：1、国内外研究现状及进展 2、苹果图像采集与处理 3、苹果大小与形状检测 4、粒子群优化的BP神经网络苹果颜色检测算法 5、遗传算法优化BP神经网络苹果缺陷检测算法 6、苹果检测系统的软件、硬件及界面设计(Research on Apple detection algorithm based on machine vision. The main contents include: 1, the domestic and foreign research present situation and the progress of 2, apple image acquisition and processing 3, the shape and size of Apple detection 4, particle swarm optimization of BP neural network in apple color detection algorithm 5, genetic algorithm optimization BP neural network for Apple defect detection algorithm 6, apple detection system software, hardware and interface design)

simulink vector control example

波达方向DOA估计的程序，其中运用了MUSIC以及两种经典的波束形成的方法（Bartlett以及CAPON)(DOA DOA estimation procedures, as well as the use of two classic MUSIC beamforming method (Bartlett and CAPON))

语音识别技术的最终目标是要让计算机能与人自由交谈。目前，连续语音识别技术正趋于成熟，语音识别也延伸出了诸多实用化的研究方向。今后，语音识别的重点将集中在自然话语识别与理解、实时语音识别和语音识别鲁棒性等方面。作为一门交叉学科，语音识别所涉及到的技术有信号处理、模式识别、概率论和信息论、发声机理、听觉机理和人工智能等。(The ultimate goal of speech recognition technology is to make computers and allowing others to speak freely. At present, continuous speech recognition technology is maturing, voice recognition is also extended out a lot of practical research directions. In the future, speech recognition will focus on Spontaneous Speech Recognition and Understanding, real-time speech recognition and speech recognition robustness and so on. As an interdisciplinary subject, speech recognition technology involved in a signal processing, pattern recognition, probability theory and information theory, vocal mechanism, hearing mechanism and artificial intelligence.)

it is for wave solution that is good for all persen