MATLAB Implementation of Audio Signal Processing with FFT and Noise Reduction Techniques

In your initial description, you mentioned an audio processing program incorporating FFT and noise reduction. This serves as an excellent foundation, and I'd like to demonstrate how this concept can be expanded to provide more comprehensive coverage of the subject matter.

First, you could elaborate on the operational principles of FFT and noise reduction algorithms to enhance beginners' understanding. For FFT implementation, you might explain how MATLAB's fft() function transforms time-domain signals into frequency-domain representations, enabling spectral analysis. For noise reduction, detail how threshold-based filtering or spectral subtraction techniques can be implemented using MATLAB's array operations to suppress unwanted frequency components.

Next, introduce various types of audio processing modules such as equalizers and compressors, explaining their integration with FFT and noise reduction systems. Describe how digital equalizers can be created using IIR/FIR filters with functions like filter() or firls(), while compressors can utilize dynamic range control through envelope detection and gain computation algorithms.

Additionally, provide practical implementation tips for improving audio quality, such as optimal windowing techniques for FFT analysis (using hamming() or hanning() functions) and parameter tuning strategies for noise reduction thresholds based on signal-to-noise ratio calculations.

Finally, include concrete application examples – such as implementing wind noise reduction using high-pass filtering (with functions like highpass() or designing custom Butterworth filters) or enhancing music recordings through multiband spectral processing. These examples help beginners understand practical applications of FFT, noise reduction, and other audio processing techniques for quality improvement.