Recognition and classification of Power Quality Distorted Signals (PQDSs) in power systems is an essential duty. One of the noteworthy issues in Power Quality Analysis (PQA) is identification of distorted signals using an efficient scheme. This paper recommends a Time–Frequency Analysis (TFA), for extracting features, so-called "hybrid approach", using incorporation of Multi Resolution Analysis...

objective: in this research, a new approach termed as “evolutionary-based brain map” is presented as a diagnostic tool to classify schizophrenic and control subjects by distinguishing their electroencephalogram (eeg) features. methods: particle swarm optimization (pso) is employed to find discriminative frequency bands from different eeg channels. by deploying the energy of those selected frequ...

Researchers are exploring challenging techniques for the analysis of power quality signals for the detection of power quality (PQ) disturbances. PQ disturbances have become a serious problem for the end users and electric utilities. Numerous algorithms have been developed for the classification of unstructured data. In this paper, the classification of power quality signals are performed based ...

The study of the quality of electric power lines is usually known as Power Quality. Power quality problems are increasingly due to a proliferation of equipment that is sensitive and polluting at the same time. The detection and classification of the different disturbances which cause power quality problems is a difficult task which requires a high level of engineering knowledge. Thus, neural ne...