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00758046
binary frequency shife keying amplitude modulation
- 2010-12-03 03:29:30下载
- 积分：1
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(HOSA)-Toolbox
MATLAB高阶谱分析信号处理工具箱(HOSA)(MATLAB Signal Processing Toolbox high-spectral analysis (HOSA))
- 2011-10-05 20:17:51下载
- 积分：1
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psolssvm
matlab粒子分析算法工具箱，这是最新的希望对有需要的人有用，这个是源代码(matlab particle analysis algorithm toolbox, which is the latest hope useful for people in need, this is the source code)
- 2013-05-20 19:02:20下载
- 积分：1
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thzpuhkx
加入重复控制，相关分析过程的matlab方法，各种资源分配算法实现，鲁棒性好，性能优越，这个有中文注释，看得明白，信号处理中的旋转不变子空间法，一个很有用的程序。( Join repetitive control, Correlation analysis process matlab method, Various resource allocation algorithm, Robustness, superior performance, The Chinese have a comment, understand it, Signal Processing ESPRIT method, A very useful program.)
- 2016-04-06 21:59:27下载
- 积分：1
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onduleur
some simulation of dtc coommand my name is belmhel ahmed my tel 0797611456
- 2009-05-24 23:04:46下载
- 积分：1
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MATlab
MATLAB经典书籍电子书，希望对学习matlab的朋友有用~(a book of matlab,hoping that will be useful to matlab learners.)
- 2012-04-23 20:50:08下载
- 积分：1
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saolei
扫雷，一个很好玩的游戏，matlab编码(Mine, a very fun game, matlab code)
- 2014-11-25 09:50:10下载
- 积分：1
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PSO
粒子群优化算法（PSO）是一种基于种群的随机优化技术，由Eberhart和Kennedy于1995年提出。粒子群算法模仿昆虫、兽群、鸟群和鱼群等的群集行为，这些群体按照一种合作的方式寻找食物，群体中的每个成员通过学习它自身的经验和其他成员的经验来不断改变其搜索模式。
(Particle swarm optimization algorithm (PSO) is a population based stochastic optimization technique, put forward by Eberhart and Kennedy in 1995. Particle swarm optimization (pso) algorithm on insects, herds, flocks and schools of fish swarm behavior, and these groups to find food in a cooperative way, each member of the group itself by learning experience and the experience of the other members to continuously change its search pattern.)
- 2013-04-11 17:58:49下载
- 积分：1
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QuadRotor_MA8.2
MB8四旋翼自动驾驶仪的源码，包括姿态采集，状态估计以及控制输出。不推荐直接使用，但是可以作为学习(MB8 four rotor autopilot source, including posture acquisition, state estimation and control output. Not recommended for direct use, but can be used as learning)
- 2014-01-15 16:52:27下载
- 积分：1
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matlab
y3k=fft(u,(m+n-2)/4)
i=1:(m+n-2)/4
subplot(5,2,9) stem(i,u)
title( 滤波后上采样 )
k=1:(m+n-2)/4
subplot(5,2,10) stem(k,y3k)
title( 上采样频谱 )
xlabel( k ) ylabel( y3k ) (y3k = fft (u, (m+ n-2)/4) i = 1: (m+ n-2)/4 subplot (5,2,9) stem (i, u) title (after filtering the sample) k = 1: (m+ n-2)/4 subplot (5,2,10) stem (k, y3k) title (on the sample spectrum) xlabel (k) ylabel (y3k))
- 2009-01-06 13:09:09下载
- 积分：1
