Fault detection is a key tool to ensure the safety and reliability of machinery. In machinery
fault detection, signal processing methods are extensively applied to extract fault …

Extracting ship-radiated line signatures from intense background noise presents a
significant challenge in remote passive sonar detection and identification. While stochastic …

Stochastic resonance (SR) has been widely concerned and studied in the field of
mechanical fault detection due to the capability of weak signal detection. However, research …

The mean first-passage time (MFPT) and the weak signal detection method of stochastic
resonance (SR) on multi-stable nonlinear system under color correlated noise are studied …

For early mechanical fault diagnosis, stochastic resonance (SR) breaks the previous
perception that “noise is useless” and uses internal noise or external noise to enhance weak …

Parrondo's games to date have largely focused on the dynamics of capital mean, and not
capital spread—the potential of the framework in modelling ecological and socioeconomic …

We investigate the stochastic resonance phenomenon in a discrete Hopfield neural network
for transmitting binary amplitude modulated signals, wherein the binary information is …

Early fault diagnosis is a hot topic in the field of fault diagnosis. The collected vibration
signals containing weak fault information are difficult to extract fault features due to the …

Gearboxes are widely used in engineering machinery, but tough operation environments
often make them subject to failure. And the emergence of periodic impact components is …

Signal denoising has been significantly explored in various engineering disciplines. In
particular, structural health monitoring applications generally aim to detect weak anomaly …