The NTIS website and supporting ordering systems are undergoing a major upgrade from 8PM on September 25th through approximately October 6. During that time, much of the functionality, including subscription and product ordering, shipping, etc., will not be available. You may call NTIS at 1-800-553-6847 or (703) 605-6000 to place an order but you should expect delayed shipment. Please do NOT include credit card numbers in any email you might send NTIS.
Documents in the NTIS Technical Reports collection are the results of federally funded research. They are directly submitted to or collected by NTIS from Federal agencies for permanent accessibility to industry, academia and the public.  Before purchasing from NTIS, you may want to check for free access from (1) the issuing organization's website; (2) the U.S. Government Printing Office's Federal Digital System website; (3) the federal government Internet portal; or (4) a web search conducted using a commercial search engine such as
Accession Number ADA571140
Title Kernel Multi-Metric Learning for Multi-Channel Transient Acoustic Signal Classification.
Publication Date Mar 2012
Media Count 4p
Personal Author H. Zhang N. M. Nasrabadi T. S. Huang Y. Zhang
Abstract In this paper, we propose a kernel multi-metric learning algorithm for multi-channel transient acoustic signal classification. The proposed method learns a set of metrics jointly for multi-channel transient acoustic signals in a kernel-induced feature space to exploit the non-linearity of the data for improving the classification performance. An effective algorithm is developed for the task of learning multiple metrics in the kernel space. By learning the multiple metrics jointly within a single unified optimization framework, we can learn better metrics to integrate the multiple channels of the signal for a joint classification. Experimental results compared with classical as well as recent algorithms on real-world acoustic datasets verified the effectiveness of the proposed method.
Keywords Acoustic signals
Foreign reports
Kernel learning
Metric learning
Multichannel acoustic signal classification

Source Agency Non Paid ADAS
NTIS Subject Category 46A - Acoustics
Corporate Author Northwestern Polytechnical Univ., Xian (China). School of Computer Science.
Document Type Technical report
Title Note Conference paper.
NTIS Issue Number 1315
Contract Number W911NF-09-1-0383

Science and Technology Highlights

See a sampling of the latest scientific, technical and engineering information from NTIS in the NTIS Technical Reports Newsletter

Acrobat Reader Mobile    Acrobat Reader