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BLDC_SMVSC
无刷直流电动机的滑模变结构控制程序－采用变速PVC策略 (brushless DC motor SMVSC control procedures-using variable speed PVC strategy)
- 2007-03-23 23:59:53下载
- 积分：1
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circuit-system-analysis-by-MATLAB
应用MATLAB 进行电路功能、信号系统的分析。(Application of MATLAB circuit function analysis of the signal system.)
- 2013-01-25 10:53:35下载
- 积分：1
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LEACH_Matlab_Code
使用matlab仿真的无线传感器网络LEACH协议(LEACH protocol for wireless sensor networks using matlab simulation)
- 2013-04-06 23:23:00下载
- 积分：1
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[Draguna_Vrabie-_Kyriakos_G._Vamvoudakis-_Frank
Optimal Adaptive
Control and
Differential Games
by Reinforcement
Learning Principles
- 2015-04-07 13:30:48下载
- 积分：1
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SARFIA_Matlab
thresholding_demo.m interactively loads an image stack, performs thresholding based on the Laplace operator and extracts time-series information from the image stack based on a binary mask provided by the thresholding operation.
- 2010-01-27 20:47:09下载
- 积分：1
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matlab16QAM
matlab实现16QAM的调盒解调(matlab achieve 16QAM modulation demodulator box)
- 2008-01-06 17:40:32下载
- 积分：1
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Untitled
最炫民族风（凤凰传奇）旋律的MATLAB程序形式(MATLAB program in the form of the melody of the coolest Ethnic (Phoenix legend))
- 2013-03-11 10:33:25下载
- 积分：1
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WindyGridWorldQLearning
Q-learning (Watkins, 1989) is a simple way for agents to learn how to act optimally in controlled Markovian
domains. It amounts to an incremental method for dynamic programming which imposes limited computational
demands. It works by successively improving its evaluations of the quality of particular actions at particular states.
This paper presents and proves in detail a convergence theorem for Q,-learning based on that outlined in Watkins
(1989). We show that Q-learning converges to the optimum action-values with probability 1 so long as all actions
are repeatedly sampled in all states and the action-values are represented discretely. We also sketch extensions
to the cases of non-discounted, but absorbing, Markov environments, and where many Q values can be changed
each iteration, rather than just one.
- 2013-04-19 14:23:35下载
- 积分：1
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Kmeans_test
K-Means聚类算法，内附参考文献，亲测可用，性能良好，效果极为明显，完全适用于各种数据维度的数据集分类，欢迎下载使用。(K-Means clustering algorithm, pro-test available.)
- 2019-03-29 20:47:26下载
- 积分：1
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1280fft
1280点fft变换，改变传统的需2046点FFT的情况。(1280 point FFT，radix 4 and radix 5 )
- 2010-11-07 23:05:19下载
- 积分：1
