Sequential Locally Optimum Test (SLOT): A Sequential Detection Scheme Based on Locally Optimum Test Statistic
Jinsoo Bae, Seong Ill Park, Yun Hee Kim, Seokho Yoon, Jongho Oh, Iickho Song, Seong‐Jun Oh
Abstract
Jinsoo Bae, Seong Ill Park, Yun Hee Kim, Seokho Yoon, Jongho Oh, Iickho Song, Seong‐Jun Oh
Abstract
Based on the characteristics of the thresholds of two detection schemes employing locally optimum test statistics, a sequential detection design procedure is proposed and analyzed. The proposed sequential test, called the sequential locally optimum test (SLOT), inherently provides finite stopping time (terminates with probability one within the finite horizon), and thereby avoids undesirable forced termination. The performance of the SLOT is compared with that of the fixed sample-size test, sequential probability ratio test (SPRT), truncated SPRT, and 2-SPRT. It is observed that the SLOT requires smaller average sample numbers than other schemes at most values of the normalized signal amplitude while maintaining the error performance close to the SPRT.
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Based on the characteristics of the thresholds of two detection schemes employing locally optimum test statistics, a sequential detection design procedure is proposed and analyzed. The proposed sequential test, called the sequential locally optimum test (SLOT), inherently provides finite stopping time (terminates with probability one within the finite horizon), and thereby avoids undesirable forced termination. The performance of the SLOT is compared with that of the fixed sample-size test, sequential probability ratio test (SPRT), truncated SPRT, and 2-SPRT. It is observed that the SLOT requires smaller average sample numbers than other schemes at most values of the normalized signal amplitude while maintaining the error performance close to the SPRT.
Key concepts: Sequential probability ratio test, Sequential estimation, Test statistic, Sequential analysis, Mathematics, Algorithm, Stopping time, Statistics