Channel-coding-and-interleaving

书名：Fuzzy and Neural Approaches in Engineering with MATLAB Supplement 作者 J. Wesley Hines 1997 英文。 光盘文件(Title: Fuzzy and Neural Approaches in Engineering with MATLAB Supplement author J. Wesley Hines 1997 English. CD-ROM file)

TCSC可控串联补偿装置simulink仿真(TCSC controllable series compensation device simulink simulation routine)

Is-95 反向业务信道端到端simulink仿真(Is-95 reverse traffic channel end simulink simulation)

高斯混合模型——GMM的算法，属于大数据量的数据处理(failed to translate)

单个的MIMI-OFDM系统的MATLAB的仿真，有英文注释(Single MIMI-OFDM system MATLAB simulation, with English notes)

快速泊松方程求解--MATLAB Fast Poisson Solver in a Square(Fast Poisson equation- MATLABFast Poisson Solver in a Square)

The principle of Huffman coding is (roughly) to replace symbols in the original data (in your case the value of each pixel of the image) by a numeric code that is attributed according to the probability of the symbol. The most probable (i.e. the most common) symbol will be replaced by shorter codes in order to realize a compression of the data.

单边放炮数值模拟程序，对于初学地震勘查的同行是很有用的模板。(csp modelling and the modelling of seismic in geophysics)

对时频峰值地震噪声的滤波及对实际信号的处理、(Time-frequency seismic noise on the peak of the actual signal filtering and processing,)

说明：  工程实际中的许多优化问题是多目标的优化设计问题。通常情况下多个目标是处于冲突状态的,不存在一个最优设计使所有的目标同时达到最优,一个目标性能的改善,往往以其它一个或多个目标性能的降低为代价。无论采用自适应遗传算法还是其它在标准遗传算法基础上经过改进的遗传算法,如果采用加权组合法等将多目标转化为单目标的处理方法,就无法充分发挥遗传算法的优势。如果把遗传 算法与适用于多目标处理的几此协方法相结合,就能完全发挥遗传算法在多目标优化设计中的作用。(Many optimization problems in engineering practice are multi-objective optimization design problems. Generally, multiple goals are in conflict. There is no one optimal design to achieve all goals simultaneously. The improvement of one goal's performance is often at the expense of the performance of one or more other goals. Whether adaptive genetic algorithm or other improved genetic algorithm based on standard genetic algorithm is adopted, if weighted combination method is adopted to transform multi-objective into single-objective processing method, the advantages of genetic algorithm cannot be fully utilized. If the genetic algorithm is combined with several cooperative methods suitable for multi-objective processing, the role of genetic algorithm in multi-objective optimal design can be fully exerted.)