IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 55, NO. 6, JUNE 2007 2757 [9] B. Zadrozny, J. Langford, and N. Abe, “Cost sensitive learning by cost- proportionate example weighting,” in Proc. 3rd Int. Conf. Data Mining, Melbourne, FL, 2003, IEEE Computer Society Press. [10] P. Domingos, “MetaCost: A general method for making classifiers cost sensitive,” in Proc. 5th Int. Conf. Knowledge Discovery Data Mining, San Diego, CA, 1999, pp. 155–164, ACM Press. [11] C. Elkan, “The foundations of cost-sensitive learning,” in Proc. 17th Int. Joint Conf. Artificial Intelligence, Seattle, WA, 2001, pp. 973–978. [12] D. Margineantu, “Class probability estimation and cost-sensitive classification decisions,” in Proc. 13th Eur. Conf. Machine Learning, Helsinki, Finland, 2002, pp. 270–281. [13] B. Scholkopf and A. J. Smola, Learning with Kernels. Cambridge, MA: MIT Press, 2002. [14] C. Cortes and V. Vapnik, “Support-vector networks,” Mach. Learn., vol. 20, no. 3, pp. 273–297, 1995. [15] T. M. Cover and P. E. Hart, “Nearest neighbor pattern classification,” IEEE Trans. Inf. Theory, vol. IT-13, no. 1, pp. 21–27, 1967. [16] T. Joachims, “Making large-scale SVM learning practical,” in Ad- vances in Kernel Methods—Support Vector Learning. Cambridge, MA: MIT Press, 1999. [17] C. C. Chang and C. J. Lin, “LIBSVM: A Library for Support Vector Machines,” 2001 [Online]. Available: http://www.csie.ntu.edu.tw/ ~cjlin/libsvm Comments on “Detection of Distributed Sources Using Sensor Arrays” Sridhar Ramakrishnan, Student Member, IEEE, and Satish Udpa, Fellow, IEEE Abstract—In the above correspondence (Y. Jin and B. Friedlander, “Detection of distributed sources using sensor arrays,” IEEE Trans. Signal Process., vol. 52, no. 6, pp. 1537–1548, June 2004), Jin and Friedlander develop a GLR-based detector for detecting a random spatially distributed signal source using an array of sensors. We show that the expression for required SNR (RSNR) has been incorrectly derived, which has led the au- thors to draw incorrect conclusions in their work. In this correspondence, we correct this particular error and a few other typographical errors, and provide appropriate conclusions to the original work. Index Terms—Distributed source, sensor array, signal detection. In the above correspondence, [1, eq. (50)] expresses the required SNR (RSNR) incorrectly as (1) The expression for RSNR when derived correctly should read as (2) Manuscript received March 10, 2006; revised July 15, 2006. The associate editor coordinating the review of this manuscript and approving it for publica- tion was Dr. Fulvio Gini. The authors are with the Electrical and Computer Engineering Department, Michigan State University, East Lansing, MI 48824 USA (e-mail: rsridhar@egr. msu.edu; udpa@egr.msu.edu). Digital Object Identifier 10.1109/TSP.2007.893740 Fig. 1. Normalized RSNR versus degrees of freedom ( , ) for different target and . A simplified form of the above expression is obtained when we consider the case where all the principal eigenvalues of are approximately equal, i.e., , . Defining as the degrees of freedom, we, thus, obtain RSNR (3) instead of RSNR (4) as expressed in [1]. Consequently, the expression for output SNR de- fined as RSNR SNRG becomes RSNR SNRG (5) as opposed to RSNR SNRG (6) mentioned as [1, eq. (51)] in the original work by Jin and Friedlander. As a result of the incorrect expression in (4), Fig. 8 in the original correspondence, i.e., the plot of RSNR versus degrees of freedom for different , fails to capture the variation in the RSNR performance for changing (number of time snapshots) and changing (effective rank of , which is a measure of the angular spread of the signal), independently. The figure would be correct only under a special case of snapshot, and not in general for all . The number of degrees of freedom contains information of both and , but the effect of increasing on RSNR ( , being held constant at different values) is markedly different from the effect of increasing ( , being held constant at different values) on RSNR. Figs. 1–4 in this correspondence depict this variation in the RSNR performance for four different cases. 1053-587X/$25.00 © 2007 IEEE