Polyphase Filtering in Signal Processing

In signal processing, polyphase filtering serves as a prevalent technique for handling diverse signal types and effectively extracting valuable information from signals. This method finds applications across multiple domains including audio processing, image manipulation, and communication systems. The core implementation involves decomposing a single filter into multiple parallel subfilters (polyphase components) that operate at reduced sampling rates, typically using polyphase decomposition algorithms. Each subfilter processes specific phases of the input signal through techniques like phased FIR filter banks, enabling efficient computational structures for interpolation and decimation operations. By employing different filter configurations, polyphase filtering facilitates customized signal processing outcomes, making it particularly valuable for multirate systems where computational efficiency is critical. Consequently, polyphase filtering plays a vital role in modern signal processing workflows and sees extensive adoption across various application scenarios.