matlab-program-design

本文件含有关于matlab学习的资料，适用于初学者(This document contains information on learning matlab for beginners)

说明：  混沌时间序列 多步预测－－多步预测问题(Chaotic time series multi-step prediction- the issue of multi-step prediction)

试过，可以。遗传算法源代码，来自一本matlab书，在这分享(genetic algorithm)

CCSDS 131.1-O-2 ORENGE标准中的LDPC编译码误码率曲线(Error rate of LDPC based on CCSDS 131.1-O-2 ORENGE standard)

matlab的web开发，配置matlab web server(develop matlab using web)

MATLAB关于FFT频谱分析的程序,可以实现信号的频谱分析(MATLAB on the FFT spectrum analysis procedures, spectral analysis of the signal can be achieved)

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.)

内含visual C++和MATLAB代码，利用高斯呼喝模型进行背景建模，自适应确定高斯分量的个数，由Z.Zivkovic开发，相关文章是 Improved adaptive Gausian mixture model for background subtraction(Containing visual C++ and MATLAB code, the use of Gaussian background modeling feeding model, adaptive determine the number of Gaussian components, developed by Z.Zivkovic related article Improved adaptive Gausian mixture model for background subtraction)

Numerical program on Newton’s forward difference formulae, the use of Sterling formulae & the use of Newton’s backward difference formulae combindly, Trapezoidal rule, Gauss-Seidal method, Jacobi method.

给出了信号压缩通常的变换-量化-编码函数。DHT函数为离散DHT变换，是FFT变换的近似，其正反变换相同，克服了FFT复系数不利于存储的缺点。LLMAX函数给出了某x序列在固定比特下的最佳量化输出。熵编码函数为霍夫曼编码。(Gives the signal compression usually transform- quantitative- coding function. DHT DHT discrete transform function, the FFT transform approximation, the same positive and negative transformation, overcoming complex FFT coefficient is not conducive to storage shortcomings. LLMAX function x is given a fixed bit sequence in the optimum quantized output. Entropy coding function as Huffman coding.)