  We use a multifractal formalism to study the effect of stochastic resonance
in a noisy bistable system driven by various input signals. To characterize the
response of a stochastic bistable system we introduce a new measure based on
the calculation of a singularity spectrum for a return time sequence. We use
wavelet transform modulus maxima method for the singularity spectrum
computations. It is shown that the degree of multifractality defined as a width
of singularity spectrum can be successfully used as a measure of complexity
both in the case of periodic and aperiodic (stochastic or chaotic) input
signals. We show that in the case of periodic driving force singularity
spectrum can change its structure qualitatively becoming monofractal in the
regime of stochastic synchronization. This fact allows us to consider the
degree of multifractality as a new measure of stochastic synchronization also.
Moreover, our calculations have shown that the effect of stochastic resonance
can be catched by this measure even from a very short return time sequence. We
use also the proposed approach to characterize the noise-enhanced dynamics of a
coupled stochastic neurons model.
