Finite-Length Bounds on Hypothesis Testing Subject to Vanishing Type I Error Restrictions

• Published in: IEEE signal processing letters Vol. 28; pp. 229 - 233
• Main Authors: Espinosa, Sebastian, Silva, Jorge F., Piantanida, Pablo
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Computer Science; concentration inequalities; Constrictions; Context; Convergence; Error analysis; Error exponent; Error probability; Errors; False alarms; finite-length analysis; Hypotheses; Hypothesis testing; Lower bounds; Numerical analysis; performance bounds; Probability; Restrictions; Upper bound; Hypothesis testing performance bounds finitelength analysis error exponent concentration inequalities; Hypothesis testing; concentration inequalities; performance bounds; error exponent; finitelength analysis

A central problem in Binary Hypothesis Testing (BHT) is to determine the optimal tradeoff between the Type I error (referred to as false alarm) and Type II (referred to as miss) error. In this context, the exponential rate of convergence of the optimal miss error probability - as the sample size ten...