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[Other resourceloadcode

Description: 在MATLAB中编写实现图像的不同级别小波分解算法;2选择合适的小波基;3对经典的几幅黑白和彩色图像进行DWT变换;4实现零树、基于塔式网格矢量量化、基于LBG算法、基于标量量化等小波变换编码;5得到分析比较结果。达到的目的:1综合训练学生编程的能力;2对高数、计算方法、程序设计、数据结构、算法、数字图像处理等课程的复习和运用;3可培养学生的算法设计和分析能力。-in MATLAB prepared to achieve different levels of image wavelet decomposition algorithm; Choice of two small Porgy; Three pairs of classic pieces of black-and-white and color images DWT; Four zero tree, grid-based Tower vector quantization, LBG-based algorithm, based on the scalar quantization Wavelet Transform Coding ; 5 analyzed the results of the comparison. The purpose : a comprehensive training program students; Two pairs of the high number and the method of computation, programming, data structures, algorithms, digital image processing and review of the curriculum used; Three students can develop the algorithm design and analysis.
Platform: | Size: 34727 | Author: aa | Hits:

[matlabloadcode

Description: 在MATLAB中编写实现图像的不同级别小波分解算法;2选择合适的小波基;3对经典的几幅黑白和彩色图像进行DWT变换;4实现零树、基于塔式网格矢量量化、基于LBG算法、基于标量量化等小波变换编码;5得到分析比较结果。达到的目的:1综合训练学生编程的能力;2对高数、计算方法、程序设计、数据结构、算法、数字图像处理等课程的复习和运用;3可培养学生的算法设计和分析能力。-in MATLAB prepared to achieve different levels of image wavelet decomposition algorithm; Choice of two small Porgy; Three pairs of classic pieces of black-and-white and color images DWT; Four zero tree, grid-based Tower vector quantization, LBG-based algorithm, based on the scalar quantization Wavelet Transform Coding ; 5 analyzed the results of the comparison. The purpose : a comprehensive training program students; Two pairs of the high number and the method of computation, programming, data structures, algorithms, digital image processing and review of the curriculum used; Three students can develop the algorithm design and analysis.
Platform: | Size: 34816 | Author: aa | Hits:

[AI-NN-PRJava_neuralnetwork_toolkit

Description: 本工具包主要是为对神经网络有兴趣人士提供的一种方便,灵活的学习和研究软件。 JNNT由java语言写成,具有跨平台的优越性能.java applet的演示版更简单到只需要任何机器上的浏览器就可以运行,无需安装任何大型附加软件。更方便爱好者通过internet远程访问资源。 支持反向传播算法(BP),LBG聚类法和径向基网络(RBF) -This toolkit is for people interested in neural networks has provided a convenient, flexible learning and research software. JNNT by the java language, cross-platform with superior performance. Java applet demo version is more simple to just any machine can run a browser, without installing any large-scale add-on software. Enthusiasts through the internet more convenient remote access to resources. To support the back-propagation algorithm (BP), LBG clustering method and radial basis function network (RBF)
Platform: | Size: 32768 | Author: 林盈 | Hits:

[GUI DevelopLBG

Description: Linde, Buzo, and Gray (LBG) proposed a VQ design algorithm based on a training sequence. The use of a training sequence bypasses the need for multi-dimensional integration. The LBG algorithm is of iterative type and in each iteration a large set of vectors, generally referred to as training set, is needed to be processed. Usually, vectors sampled from a group of typical signals to be encoded altogether construct a training set T={x1,x 2,?.x M} ,where xi represents a sampled training vector and M represents the size of training set which is far greater than the codebook size N.
Platform: | Size: 87040 | Author: 龙鹏 | Hits:

[matlabvqlbg

Description: 语音信号处理矢量量化的LBG算法,又称K-mean 算法-in speech signal process vector quantization technology using LBG algorithm with matlab language
Platform: | Size: 1024 | Author: renfangqin | Hits:

[matlab59159000-Speaker-Recognition-Using-MATLAB

Description: speaker recognition.In 1980, Linde, Buzo, and Gray (LBG) proposed a VQ design algorithm based on a training sequence. The use of a training sequence bypasses the need for multi-dimensional integration. A VQ that is designed using this algorithm are referred to in the literature as an LBG-VQ.
Platform: | Size: 2380800 | Author: arun | Hits:

[Speech/Voice recognition/combine语音聚类示例

Description: 实验示例是基于语音中的mfcc,语音倒谱特征来进行聚类,先利用训练样本来计算训练样本聚类中心(用到了lbg算法),之后再进行分类。 注意:使用代码时需要自己更改文件路径。(This example is based on the MFCC in speech and the feature of speech Cepstrum to cluster. First, the training sample is used to calculate the training sample clustering center (using the LBG algorithm), then the classification is then carried out.)
Platform: | Size: 1129472 | Author: 啦丿啦 | Hits:

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