International Journal of Science, Engineering and TechnologyAuthors: Prof.K.M. Jadhav, Mrs.Nikita Suryawanshi, Mrs Sandya Shinde, Mrs.Sneha Shinde, Mr.Rohit Raychure, Mr.suraj Dhanvade, Mr Shridhar Gurav, Mr.Shrikant Chavan, Mr.Rohan Dabade
Abstract: Artificial Intelligence (AI)-based signal processing techniques combine advanced mathematical models with machine learning algorithms to improve the analysis, interpretation, and optimization of signals in various applications such as communication, healthcare, and image processing. These techniques use mathematical foundations including linear algebra, probability theory, optimization, Fourier transforms, and neural network architectures to process complex datasets efficiently. AI methods such as deep learning, adaptive filtering, and pattern recognition enhance traditional signal processing by enabling automatic feature extraction, noise reduction, and predictive analysis. Mathematical analysis plays a crucial role in evaluating algorithm performance, convergence, computational complexity, and accuracy. By integrating AI with signal processing, modern systems achieve higher precision, faster decision-making, and improved adaptability, making these techniques essential for next-generation technological advancements.
DOI: http://doi.org/10.5281/zenodo.20560052
