modoptimization

VSharp学习软件源代码WindowsApplication_Example示例程序(VSharp learning software WindowsApplication_Example sample application source code)

滑模经典论文a control engineer s guide to sliding mode control(Slipform classic paper a control engineer s guide to sliding mode control)

code for inserting ext in image

snr calculation based on FFT

Griewank测试函数，经过实验已经可以使用，现在分享给大家啊(Griewank test function, after the experiment has been can now share with you ah)

jade algorithm for extration of features

simulink学习教材，快速学会simulink的基本使用(Simulink learning materials, basic use quickly learn to simulink)

自适应均衡领域的经典算法，最小均方误差算法（LMS）算法的数字均衡器建模源代码。建模建立了一个通信系统的收发两端，并模拟了信道衰减和噪声。并在接收端使用了数字均衡器。主程序中一次在接收端使用了自适应均衡器，另一次没有使用，可以清楚看到均衡前后误码率的差别。(The field of classical adaptive equalization algorithm, the minimum mean square error algorithm (LMS) algorithm for modeling digital equalizer source code. Modeling the establishment of sending and receiving ends of a communication system, and simulate the channel attenuation and noise. And at the receiving end using a digital equalizer. Once the main program at the receiving end using adaptive equalizer, another did not use, you can clearly see the difference before and after the equalizer BER.)

利用matlab中的simulink仿真，建立了定轴齿轮和行星齿轮的的仿真模型(Using the simulink of matlab, the establishment of a fixed axis gear and planetary gear simulation model)

说明：  通过并行压缩进行二维信号压缩，提出了一种利用并行压缩传感技术对二维信号进行压缩的新方案。根据这个原理，译码器的重新构造可以并行进行。通过对二维信号进行某些排列，可以确保所有列具有大致相同的密度级别，并且可以使用相同的测量矩阵进行采样。这样可以避免二维信号的矢量化，从而大大减小测量矩阵的尺寸。我们证明，如果排列良好，重建均方误差的上限会更紧。为了说明这一方案，我们将其应用于视频压缩并使用不同帧的排列有两种：参考帧的基于Z字形扫描的排列和非参考帧的基于块测试的排列。仿真结果表明，在相同的压缩比下，峰值信噪比比比在无置换情况下可提高3-7db左右。(we propose a new scheme to compress 2D signals using parallel compressed sensing. According to this seheme, the reeonstruction at the decoder can be performed in parallel. By performing certain permutation on a 2D signal, all columns are insured to have approximately the same density level and can be sampled using the same measurement matrix. In this way, vectorization of a 2D signal can be avoided, and thus the size of the measurement matrix can be dramatically reduced. We prove that with a good permutation, we can have a tighter upper bound on reconstruction mean square error. To illustrate this scheme, we apply it to video compression and use two kinds of permutations for different frames: the zigzag-scanbased permutation for reference frames and the block-test-based permutation for non-reference frames. Simulation results show that under the same compression ratio, the peak signal-to-noise ratio can be improved by approximately 3-7 dB compared to the case without permutation.)