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文章基本信息

  • 标题:Validity-Guided Fuzzy Clustering Evaluation for Neural Network-Based Time-Frequency Reassignment
  • 本地全文:下载
  • 作者:Imran Shafi ; Jamil Ahmad ; Syed Ismail Shah
  • 期刊名称:EURASIP Journal on Advances in Signal Processing
  • 印刷版ISSN:1687-6172
  • 电子版ISSN:1687-6180
  • 出版年度:2010
  • 卷号:2010
  • DOI:10.1155/2010/636858
  • 出版社:Hindawi Publishing Corporation
  • 摘要:

    This paper describes the validity-guided fuzzy clustering evaluation for optimal training of localized neural networks (LNNs) used for reassigning time-frequency representations (TFRs). Our experiments show that the validity-guided fuzzy approach ameliorates the difficulty of choosing correct number of clusters and in conjunction with neural network-based processing technique utilizing a hybrid approach can effectively reduce the blur in the spectrograms. In the course of every partitioning problem the number of subsets must be given before the calculation, but it is rarely known apriori, in this case it must be searched also with using validity measures. Experimental results demonstrate the effectiveness of the approach.

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