A Review on Applications of the Wavelet Transform Technique in Spectral Analysis

doi:10.4172/2168-9679.1000224

Cited by 3 publications

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Deep Learning Techniques for Photovoltaic Solar Tracking Systems: A Systematic Literature Review

Phiri

Mulenga

Zimba

et al. 2023

Preprint

View full text Add to dashboard Cite

Although photovoltaic (PV) panels are extensively used to convert solar energy into electric energy, the continuous change in the sun's angle with reference to the earth's surface limits their capacity to collect sufficient energy. To improve efficiency, solar trackers are used to constantly adjust the PV panels towards the sun to maximize energy capture. There has been an increase in the use of deep learning (DL) in solar tracking systems as it has proven to be one of the most efficient techniques owing to its success in related fields. Although there are several studies on different designs of solar tracking systems, a synthesis of the state-of-art knowledge is lacking in the literature. Therefore, this study carried out a review of the DL methods used in solar tracking systems. Specifically, dataset usage, preprocessing methods, feature engineering methods, DL algorithms and the performance metrics used in the identified studies. The review considered the studies published from 2012 to 2022. In the initial search, 5,724 articles were selected from 7 digital libraries. Only 37 academic papers were included in the review based on the inclusion criteria. The results revealed that deep hybrid learning models were the most popular among researchers. Further, the study identified research challenges and future directions relating to the availability of DL-based PV solar tracking with respect to datasets, image data, data normalization, data decomposition, and feature engineering methods. This work will be resourceful to current and future researchers in addressing the trends and challenges related to the application of DL in PV solar trackers.

show abstract

Deep Learning Techniques for Photovoltaic Solar Tracking Systems: A Systematic Literature Review

Phiri

Mulenga

Zimba

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Wavelet Transform-Based UV Spectroscopy for Pharmaceutical Analysis

Dinç

Yazan

2018

Front. Chem.

View full text Add to dashboard Cite

In research and development laboratories, chemical or pharmaceutical analysis has been carried out by evaluating sample signals obtained from instruments. However, the qualitative and quantitative determination based on raw signals may not be always possible due to sample complexity. In such cases, there is a need for powerful signal processing methodologies that can effectively process raw signals to get correct results. Wavelet transform is one of the most indispensable and popular signal processing methods currently used for noise removal, background correction, differentiation, data smoothing and filtering, data compression and separation of overlapping signals etc. This review article describes the theoretical aspects of wavelet transform (i.e., discrete, continuous and fractional) and its characteristic applications in UV spectroscopic analysis of pharmaceuticals.

show abstract

MathNet: Haar-Like Wavelet Multiresolution-Analysis for Graph Representation and Learning

Zheng¹,

Zhou²,

Li³

et al. 2020

Preprint

View full text Add to dashboard Cite

A Review on Applications of the Wavelet Transform Technique in Spectral Analysis

Cited by 3 publications

References 44 publications

Deep Learning Techniques for Photovoltaic Solar Tracking Systems: A Systematic Literature Review

Deep Learning Techniques for Photovoltaic Solar Tracking Systems: A Systematic Literature Review

Wavelet Transform-Based UV Spectroscopy for Pharmaceutical Analysis

MathNet: Haar-Like Wavelet Multiresolution-Analysis for Graph Representation and Learning

Contact Info

Product

Resources

About