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采用MATLAB进行飞行器加速设计的源码,来自于某国外网站(Accelerating aircraft design)

此程序主要演示通道间幅度误差对DBF旁瓣电平的影响。(This program is mainly to demonstrate of effect of channel amplitude errors on the sidelobes of DBF.)

随机游走类似布朗运动，就是随机的向各个方向走吧。 虽然代码没什么技术含量，不过产生的图像实在太漂亮了，所以还是贴上来吧。 产生的图像：(Similar to Brownian motion random walk, is random and go in all directions. Although the code is no technical content, but the resulting image is too beautiful, so it is still Tieshanglai it. graphics layer.)

试设计一个切比雪夫I型高通数字滤波器，采样率为8000Hz,fp=1000Hz,fs=700Hz,Rp=3dB,Rs=20dB。(Try to design a type I Chebyshev high-pass digital filter sampling rate of 8000Hz, fp = 1000Hz, fs = 700Hz, Rp = 3dB, Rs = 20dB.)

reduction to papr in ofdm with Peak Windowing: The basic idea of peak windowing is to multiply the envelope of OFDM signal with a weighting function . Therefore, ~xE (t)= xE (t) f (t) where XE(t) =[x(t)] The weighting function given by: f (t)= 1-Σ α .w(t- t ) t-t w(t) : is the window function. t : denotes the position of a local maximum of the envelop xE(t) . α : attenuation constant . When the amplitude of envelop amplitude of the OFDM signal exceeds a threshold, a window function is applied to the envelop of the OFDM signal to eliminate the peak amplitude. windowing results in a smooth signal. Hanning window function will be used for w(t) As a matter of fact , other windows such as cosine, hamming and Kaiser may be employed.

基于SMI算法的零陷展宽算法，能够有效展宽信号方向图的零陷位置(Based on the SMI algorithm, the zero broadening algorithm can effectively widen the zero position of the signal pattern)

Analiza widmowa a sygnal

排课问题是一个有约束的、多目标的组合优化问题，并且已经被证明是一个NP完全问题。 遗传算法借鉴生物界自然选择和自然遗传机制，使用群体搜索技术，尤其是用于处理传统搜索方法难以解决的复杂的和非线性的问题。经过近40年的发展，遗传算法在理论研究和实际应用中取得了巨大的成功，本文将遗传算法用于排课问题的求解，首先讨论了排课问题中的影响因素、主要约束条件、求解目标和难点，并用数学模型完整地描述了排课问题。其次对多个模糊排课目标进行了定量分析，建立了排课优化目标空间。针对排课问题研究了染色体编码方式以及遗传算子的设计，提出了适应度函数的计算方法。最后对排课问题进行了实验。实验结果表明，其过程的目标值跟踪显示，算法稳健趋优，所得结果令人满意。(Course Scheduling problem is a constrained, multi-objective optimization problem, and has proven to be a NP complete problem. Genetic algorithms reference biosphere and the natural genetic mechanism of natural selection, using the group search technology, particularly the traditional search methods for handling complex and difficult to solve nonlinear problems. After nearly 40 years of development, the genetic algorithm in the theoretical study and practical application was a great success, this paper genetic algorithm for solving the course timetabling problem, first discussed the impact of factors in the course arrangement, the main constraints, to solve goals and difficulties, and a complete mathematical model to describe the course arrangement. Arranging multiple fuzzy goals followed by a quantitative analysis, the optimal target Arranging space. Arranging for the Study of the chromosome coding and genetic operators design, proposed fitness function is calculated. Finally, the co)

Kode Program Algoritma Nearest Neighbor

说明：  利用遗传算法对BP神经网络进行了优化，避免陷于局部最优解。直接修改data数据(Genetic algorithm is used to optimize BP neural network to avoid falling into local optimal solution. Modify data data directly)