A Review of the Challenges of Adaptive Filtering Technology in High-fidelity Audio Signal Processing

Abstract

Abstract. High-fidelity audio signal processing plays an important role in modern audio technology. With the increasing demand for this technology in various audio application scenarios, the optimization of adaptive filters has emerged as a significant challenge in this field. This paper focuses on improving the performance of adaptive filters in high-fidelity audio signal processing which aims to improve the adaptability and efficiency of filters in complex audio environments by improving algorithms. In this study, the adaptive filtering algorithm based on wavelet transform and particle swarm optimization is used to verify the audio data processing by simulation and real data processing. The research data was collected using the standard audio signal database and the actual collected high-fidelity audio samples. The results show that the improved adaptive filter can significantly improve the performance of complex audio environments, improve the clarity and fidelity of audio signals and reduce the computational complexity. It is also suitable for real-time processing scenarios with limited resources. The conclusion shows that this method provides an efficient solution for high-fidelity audio signal processing and has a wide application prospect.