搜索资源列表
me2svm
- 将最大熵的数据格式转为SVM分类器所需的数据格式-of maximum entropy data formats SVM classifier to the required data format
C4_5.m
- his algorithm was proposed by Quinlan (1993). The C4.5 algorithm generates a classification-decision tree for the given data-set by recursive partitioning of data. The decision is grown using Depth-first strategy. The algorithm considers all the poss
Bayesian-machine-learn-data-mining
- 贝叶斯（Bayesion）机器学习相互信息。用于求取熵、联合熵等。改进后可用于随机反演-Bayesian (Bayesion) machine learning of mutual information. Used to obtain entropy, joint entropy and so on. Improved can be used for stochastic inversion
evlmem
- 最大熵法实现功率谱估计，内附算法实例及数据结果。-Maximum entropy power spectrum estimation method, containing the results of algorithm and data examples.
9854125413
- 运动估计是视频编码的关键技术，其最基本的原理是利用相邻帧间的时间 相关性，通过预测来减少时间冗余度。在实际编码中，为了节省码率，并不传 输每一帧的全部数据，而是利用运动估计求出每一帧与其预测参考帧之间的差 值。运动估计越准确，差值的分布越趋近与零，差值块的能量越小，经过变换、 量化和熵编码后所产生的码流的比特位率也越少。因此，运动估计搜索的准确 程度直接影响到了编码的压缩性能。 -Motion estimation is the key to video encodin
ENCLUS
- Entropy Based Subspace Clustering for Mining Data - ENCLUS - a new version of PROCLUS algorithm for clustering high dimensional data set.-Entropy Based Subspace Clustering for Mining Data- ENCLUS- a new version of PROCLUS algorithm for clustering hi
ApEn
- To estimate approximate entropy for EEG signal or time series data
KECA
- Kernel Entropy Component Analysis,KECA方法的作者R. Jenssen自己写的MATLAB代码，文章发表在2010年5月的IEEE TPAMI上面-Kernel Entropy Component Analysis, by R. Jenssen, published in IEEE TPAMI 2010. We introduce kernel entropy component analysis (kernel ECA) as a new method
Entropy
- Entropy R.Data This is an implementation of Entropy in R.
entropy
- entropy program that is a data for a test for a value of entropy
entropy-encoding
- 视频信号熵编码源程序 熵编码法是一种进行无损数据压缩的技术，在这个技术中一段文字中的每个字母被一段不同长度的比特(Bit)所代替。与此相对的是LZ77或者LZ78等数据压缩方法，在这些方法中原文的一段字母列被其它字母取代。 每个字母按照其出现的可能性所获得的最佳比特数取决于熵。 本程序不仅提供源程序，还提供相应的实例。-Entropy coding the video signal source for entropy coding method is a lossless data
DATA-ASSOCIATION-BASED-CE-METHODS
- 基于cross entropy最优方法对phd跟踪结果进行目标关联-Based on cross entropy method for phd optimal target tracking results associated
Fuzzy_MI(data)
- 计算Fuzzy Mutual Information and Fuzzy Entropy-calculate Fuzzy Mutual Information and Fuzzy Entropy
Entropy-coding-source-program
- 熵编码(entropy encoding)是一类利用数据的统计信息进行压缩的无语义数据流之无损编码。本章先介绍熵的基本概念，然后介绍香农-范诺(Shannon-Fano)编码、哈夫曼(Huffman)编码、算术编码(arithmetic coding)、行程编码(RLE)和LZW编码等常用的熵编码方法。 哈夫曼编码建议了一种将位元进位成整数的算法，但这个算法在特定情况下无法达到最佳结果。为此有人加以改进，提供最佳整数位元数。这个算法使用二叉树来设立一个编码。这个二叉树的终端节点代表被编码的字母
matlab-for-maximum-entropy
- 用于利用最大熵法求解数据资料服从的分布类型。并应用最小二乘法求解模型以得到最优解-Using the maximum entropy method for solving the data distribution type of obedience. And apply the least squares method to obtain the optimal solution to solve the model
Calculate-entropy
- 本程序主要计算一维数据序列的熵值，主要对数据序列进行数据分析-The program is mainly calculate entropy for one-dimensional data series
Maximum-Entropy
- In the distributed processing, where common labeled data may be not available for designing classifier ensemble, however, an ensemble solution is necessary, traditional fixed decision aggregation could not account for class prior mismatch or cl
approximate-entropy-matlab-program
- 通过近似熵函数 提取数据特征并画出曲线，可以直接运行-By approximate entropy feature extraction data and draw the curve, you can directly run
Entropy-coding
- 熵编码(entropy encoding)是一类利用数据的统计信息进行压缩的无语义数据流之无损编码。本章先介绍熵的基本概念，然后介绍香农-范诺(Shannon-Fano)编码、哈夫曼(Huffman)编码、算术编码(arithmetic coding)、行程编码(RLE)和LZW编码等常用的熵编码方法。-Entropy coding (entropy encoding) is a kind of the compressed by using the data statistics of the
entropy
- 计算时间序列数据（降雨等水文气象数据）的信息熵，可用于不确定性分析-Calculation of time-series data (rainfall and other hydro-meteorological data) information entropy can be used for uncertainty analysis