2021/05/11 by Varun Chivukula, Chivukula, V. N. Aditya Datta, Rupaj Kumar Nayak +1
Decision Sciences · Engineering · Social Sciences · #Audio and Speech Processing (eess.AS) #Diverse Research Studies Overview #Diverse Scientific and Engineering Research #FOS: Computer and information sciences #FOS: Electrical engineering #Multidisciplinary Science and Engineering Research #Signal Processing (eess.SP) #Sound (cs.SD) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2105.05938
openalex publication_date 2021/05/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Machine learning techniques nowadays play a vital role in many burning issues of real-world problems when it involves data. In addition, when the task is complex, people are in dilemma in choosing deep learning techniques or going without them. This paper is about whether we should always rely on deep learning techniques or it is really possible to overcome the performance of deep learning algorithms by simple statistical machine learning algorithms by understanding the application and processing the data so that it can help in increasing the performance of the algorithm by a notable amount. The paper mentions the importance of data preprocessing than that of the selection of the algorithm. It discusses the functions involving trigonometric, logarithmic, and exponential terms and also talks about functions that are purely trigonometric. Finally, we discuss regression analysis on music signals to justify our claim.