Ravi Tiwari

Abstract In this paper, several audio features are leveraged to improve detection accuracy through an advanced ensemble learning approach. For the extraction of diverse signal characteristics, the method uses Mel-frequency cepstral coefficients (MFCCs), statistical features, and short-time Fourier transform (STFT) features.

Abstract With the rapid growth in population, the increase in power demand has outpaced the expansion of transmission line infrastructure, often leading to overload conditions. To mitigate such challenges, Flexible AC Transmission System (FACTS) devices are widely adopted to enhance system reliability and stability. While FACTS devices significantly boost the power transfer capability of transmission lines, they can also impact the effectiveness of traditional protection relays.

Abstract This paper presents an approximate Maximum Likelihood (ML) estimation framework for estimating the damping factor in exponentially decaying complex sinusoidal signals. We derive a closed-form approximate ML estimator, explicitly noting its validity for small damping factors. Its efficiency is assessed through the derivation of the Cramer–Rao Lower Bound (CRLB), which serves as the theoretical benchmark for estimator performance.