FIR digital filters, signal processing, hardware implementation, optimization algorithms, frequency response design
Abstract
Digital Signal Processing (DSP) plays an important role in the College of Information Science and Technology & Artificial Intelligence areas such as communications, audio and video signal processing, etc. Filters as a central element solve the problems of noise suppression and signal extraction, which is signal separation and restoration. Finite impulse response (FIR) filters are often used in applications such as high-quality audio and image processing due to their linear phase, stability, and flexible frequency response design. This paper reviews FIR filter design methods, including window function methods, frequency discretization methods, and optimization algorithms, and investigates methods for their hardware implementation. Analyzing basic convolutional filter operations and the ways to increase the speed of filter operations by applying hardware platforms such as FPGAs and DSP processors will be explored to present innovative feasibility in the future development of new algorithms. The results of this study show that FIR filters have promising applications when supported by hardware technologies, especially in the implementation of higher-order filters that exhibit unique advantages.
