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本书介绍了稀疏和冗余表示,内容分两部分,共十六章。第一部分是稀疏和冗余表示的理论和数值基础,系统、条理地罗列了数据模型的理论基础、相关算法的数值部分(This book introduces the sparse and redundant representation, the content is divided into two parts, a total of sixteen chapters. The first part is the theoretical and numeric
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Linear prediction (LP) is an ubiquitous analysis
method in speech processing. Various studies have focused on
sparse LP algorithms by introducing sparsity constraints into
the LP framework. Sparse LP has been shown to be effective in
several issu
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K-SVD可以看做K-means的一种泛化形式,K-means算法总每个信号量只能用一个原子来近似表示,而K-SVD中每个信号是用多个原子的线性组合来表示的。
K-SVD通过构建字典来对数据进行稀疏表示,经常用于图像压缩、编码、分类等应用。(K-SVD can be regarded as a generalized form of K-means. The total K-means algorithm can only approximate one signal for each sem
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利用信号本身的结构特征,通过附加不同的稀疏约束,该模型利用过完备字典进行信号分解,使其表示成字典中若干原子的线性组合,从而获得数据的精简表示。(By using the structural characteristics of the signal itself and adding different sparse constraints, the model decomposes the signal into linear combinations of atoms in the dic
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本资源是3层的自编码器加上稀疏正则项约束的matlab代码。隐层激活函数选sigmoid函数,输出层选线性函数,程序中以一个标准数据集sonar为例,使用该方法可以做无监督表征学习,数据压缩,多任务学习等(This resource is a 3-layer self-encoder plus matlab code for sparse regular term constraints. The hidden layer activation function selects the sigm
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