FPGA Implementation of k NN Classifier Based on Wavelet Transform and Partial Distance Search

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• 作者：Yao-Jung Yeh ; Hui-Ya Li ; Wen-Jyi Hwang ; Chiung-Yao Fang
• 关键词：FPGA Implementation ; Partial Distance Search ; Image Processing ; Pattern Recognition ; Nonparametric Classification
• 刊名：Lecture Notes in Computer Science
• 出版年：2007
• 出版时间：2007
• 年：2007
• 卷：4522
• 期：1
• 页码：512-521
• 全文大小：628 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

A novel algorithm for field programmable gate array (FPGA) realization of kNN classifier is presented in this paper. The algorithm identifies first k closest vectors in the design set of a kNN classifier for each input vector by performing the partial distance search (PDS) in the wavelet domain. It employs subspace search, bitplane reduction and multiple-coefficient accumulation techniques for the effective reduction of the area complexity and computation latency. The proposed implementation has been embedded in a softcore CPU for physical performance measurement. Experimental results show that the implementation provides a cost-effective solution to the FPGA realization of kNN classification systems where both high throughput and low area cost are desired.