Adaptive Frequency Correction in Digital Audio Systems Using AI-Based Algorithms
Keywords:
digital audio, frequency distortion, adaptive filter, neural networks, signal restoration, DSP, AI algorithms.Abstract
In recent years, digital audio systems have become increasingly reliant on high-precision signal processing for maintaining sound quality across various environments. One of the critical challenges in such systems is frequency distortion, which occurs due to nonlinearities, phase mismatches, and imperfect transmission. This research investigates adaptive methods for detecting and correcting frequency distortions in digital audio signals using artificial intelligence (AI) algorithms. The study combines digital signal processing (DSP) principles with neural network architectures to develop a real-time correction framework. The proposed model improves the Signal-to-Noise Ratio (SNR) by up to 18% and reduces total harmonic distortion (THD) by 40%, based on experimental results obtained from MATLAB and TensorFlow simulations.
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