Log-normal distributions in gamma-ray burst time histories

We propose a new, simple but powerful algorithm to analyze the gamma-ray burst temporal structures based on identifying nonstatistical variations (''peaks'') in the time histories. Detailed analyses of the bursts from the third BATSE catalog show that similar to 30 bursts have more than 20 peaks individually. Upon identifying most of the peaks in those bursts. we show that the peak fluence S-i, and peak interval delta(i) distributions within each burst are consistent with log-normal distributions. Furthermore, we show that Gaussian (in linear space) and power-law distributions for peak fluences are ruled out, as is the Poisson distribution for peak intervals.