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threelegpwm
This is a simulink model for three phase pulse width modulated inverter
- 2012-03-25 15:59:04下载
- 积分：1
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MATLAB-
基于MATLAB的发动机功率计算优化方法研究(Engine power calculation based on MATLAB Optimization Method)
- 2013-10-22 16:06:21下载
- 积分：1
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MATLAB-function-inquiry-handbook
matlab函数速查手册 全面覆盖MATLAB的各类应用；查询方便：提供功能索引和字母索引；实例丰富：每个函数均配有实例讲解。(MATLAB function inquiry handbook)
- 2011-12-12 10:59:03下载
- 积分：1
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W5
说明： code to test the mimo system for the ML and MZ
- 2011-05-10 18:33:52下载
- 积分：1
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zfsb
基于matlab的字母识别，基于模板匹配，因为采用区域生长法，速度可能有些慢！(Base on matlab!)
- 2013-12-16 12:03:48下载
- 积分：1
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bustotalpowerdemand
基于线路参数的纯电动公交车充电功率需求期望建模(Pure electric bus line parameter modeling based on charging power needs and expectations)
- 2014-10-18 16:28:57下载
- 积分：1
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Lunar-soft-landing-control
月球软着陆控制系统综合仿真及分析,仿真了实际所需要的环境，简单，明了。(Lunar soft landing control system simulation and analysis, simulation of the actual needs of the environment, simple and clear.)
- 2021-01-28 21:28:36下载
- 积分：1
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PGZ.m
Reed Solomon decoding algorithm
- 2014-02-20 00:47:15下载
- 积分：1
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DFA和MFDFA算法的实现
DFA和MFDFA算法的实现，内有算法步骤说明，实现生物信号的处理，算法正确，结果很好。(DFA and MFDFA algorithm to achieve, there are steps describe the algorithm to achieve the biological signal processing algorithm is correct, the result is very good.)
- 2020-12-01 15:49:27下载
- 积分：1
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K-meanCluster
How the K-mean Cluster work
Step 1. Begin with a decision the value of k = number of clusters
Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following:
Take the first k training sample as single-element clusters
Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster.
Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample.
Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)
- 2007-11-15 01:49:03下载
- 积分：1
