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image_Histogram_equalization
matlab中重要的数字图像处理技术：直方均衡化，可以看出灰度图像的灰度值分布，并且去噪。(matlab important digital image processing techniques: Histogram equalization, we can see the distribution of gray-scale image of the gray value, and the de-noising.)
- 2009-11-24 11:25:28下载
- 积分：1
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threshold_compression
分层阈值化压缩方法同全局阈值化方法相比，在能量损失不是很大的情况下可以获得最高的压缩化。(Layered compression threshold method with the global threshold than in the case of energy loss is not large may be of the highest compression.)
- 2011-05-27 22:05:21下载
- 积分：1
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MATLAB-PC
matlab实现主成分分析，提取几个主成分，实现贡献计算。(matlab to achieve the principal component analysis)
- 2011-11-22 10:40:08下载
- 积分：1
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exercise
matlab problem set digital signal processing mitra
- 2012-01-14 01:21:11下载
- 积分：1
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dipum_images_ch04
dipum_images_ch04 matlab编程实例(dipum_images_ch04 matlab Programming Example)
- 2009-09-12 11:12:55下载
- 积分：1
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matab-experiment-handouts
说明： matab实验讲义，呵呵 这是我收藏的学习资料(matab experiment handouts)
- 2011-03-25 00:53:12下载
- 积分：1
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ge-alg
In this paper, an attractive approach for teaching genetic algorithm (GA) is pre-sented. This approach is based primarily on using MATLAB in implementing the genetic operators:
crossover, mutation and selection. A detailed illustrative example is presented to demonstrate that
GA is capable of finding global or near-global optimum solutions of multi-modal functions. An
application of GA in designing a robust controller for uncertain control systems is also given to
show its potential in designing engineering intelligent systems
- 2013-11-19 14:41:13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
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welchpgj2
采用不同窗函数对信号进行了WELCH谱估计，并可以做出对比分析。(Different window function of the signal spectrum estimation WELCH, and can make a comparative analysis.)
- 2009-06-06 09:35:55下载
- 积分：1
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matlab
这是一本matlab学习的最详尽的书籍，对学习matlab有极大的帮助。(This is a matlab most detailed study of the books, to learn matlab great help.)
- 2011-08-10 18:40:50下载
- 积分：1
