matlab

打开一幅图片，对其进行个性化处理，包括亮度调整，去除噪声，细节化等等(open an image,we process it personally,including intensity adjust,remove noise and so on)

single ended primary inductor converter

matlab by example. programming basics-elsevier (2013)

以前常有的调制识别程序大多是基于MATLAB的，本程序是基于C语言的实用程序，可以识别AM、FM、DSB、LSB、USB、CW、Noise等模拟调制信号的调制类型，是在实际工程中正在应用的实用程序！(Previous common modulation identification procedures are mostly based on MATLAB, and this program is based on the C language utility can identify the AM, FM, DSB, LSB, USB, CW, Noise and other analog modulation signal modulation type is the actual project utilities are being applied!)

对随机信源进行16QAM调制，送入高斯信道，解调后计算误码率(Random source for 16QAM modulation, into the Gaussian channel, demodulation error rate were calculated)

给出了GPU的最新快照，详细描述了当今最新的GPU的内部架构，以及如何利用GPU的编程技巧。另外额外探讨了如何利用GPU的计算能力完成其他计算任务（CUDA）。(This third volume of the best-selling GPU Gems series provides a snapshot of today s latest Graphics Processing Unit (GPU) programming techniques. The programmability of modern GPUs allows developers to not only distinguish themselves from one another but also to use this awesome processing power for non-graphics applications, such as physics simulation, financial analysis, and even virus detection—particularly with the CUDA architecture. Graphics remains the leading application for GPUs, and readers will find that the latest algorithms create ultra-realistic characters, better lighting, and post-rendering compositing effects. )

说明：  大家好，本程序功能是VC环境下Matlab组件后绑定的实现，希望对大家有所帮助(Hello everyone, this program features is the VC environment Matlab after the binding components to achieve, I hope all of you to help)

本程序具体描述了利用最小二乘算法对混合信号进行AR参数和其功率谱估计。(This procedure describes the use of least square algorithm for mixed signal AR parameter and its power spectrum estimation. )

用matlab实现维特比算法译码，程序简单易懂，自己编写的。(Using matlab Viterbi decoding algorithm, the program is simple and easy to understand, I have written.)

说明：  针对四维目标跟踪模型的主程序，可以用来学习仿真模型参数(2017-ITAC-A Novel Adaptive Kalman Filter With Inaccurate Process and Measurement Noise Covariance Matrices)