在分形近邻距离的基础上，提出了分形奇异值近邻距离，并把分形编码和局部奇异值分解结合起来，提高了识别率。

Fractal singular value neighbor distance is brought forward based on fractal neighbor distance. Fractal coding and local singular value decomposition are used to improve the recognition rate.

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同时为了进一步降低存局部潜在语义分类的存储空间的开销，采用半离散分解方法替代奇异值分解方法。

Meanwhile to reduce the cost of memory space, this paper takes the Semi-Discrete Decomposition Method rather than the Singular Value Decomposition.

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