type II error, is also important. A false alarm occurs when signal is declared present when the input con-Recently, the wavelet transform has been applied to the sists of only noise. This paper derives the probability problem of detecting and estimating transient signals in of false alarm for the algorithm in [4]. False alarm additive white noise. The general procedure of these algorithms is to take a discrete wavelet transform (DWT) of probability is numerically computed and compared the data, eliminate some of the DWT coefficients based to Monte Carlo simulation results. on some criteria, and then inverse DWT the remaining coefficients to obtain the transient signal estimate. Most CALCULATION OF FALSE ALARM of the research has focused on the estimation performance PROBABILITY of these algorithms. This research computes the false alarm probability on each DWT scale level for the algorithm described in (Noonan et al., Digital Signal Pro-Here we derive an expression for the false alarm cessing 3, 1993, 89-96). The false alarm probability is probability associated with the signal estimation althe probability that one or more DWT coefficients on a gorithm presented in [4]. Figure 1 shows a block difference level is nonzero.