MATLAB Code Implementation for DSP Real-Time Processing

In the field of digital signal processing (DSP), we frequently encounter requirements for real-time processing. To achieve these objectives, we can employ DSP techniques for real-time execution and utilize MATLAB simulation programs for verification. These technologies find extensive applications in speech signal processing, where they can be implemented to accomplish functions such as speech noise reduction and speech recognition. The implementation typically involves using MATLAB's Signal Processing Toolbox and DSP System Toolbox, which provide essential functions like filter design (fir1, butter), spectral analysis (fft, spectrogram), and real-time processing blocks (dsp.AudioFileReader, dsp.SpectrumAnalyzer). Key algorithms may include adaptive filtering for noise cancellation, MFCC (Mel-Frequency Cepstral Coefficients) extraction for speech recognition, and frame-based processing for real-time execution. The code structure often follows a pipeline architecture with buffer management, frame processing, and output handling components.