Practical Signal Processing for Seismology Using MATLAB

Practical Signal Processing for Seismology Using MATLAB is a didactic, application-oriented textbook that introduces the principles and methods of digital signal processing through seismic data analysis. Developed as a teaching resource for the course Digital Signal Processing and Analysis at the University of Naples Federico II, the book bridges fundamental signal processing theory with practical implementation in MATLAB. In modern seismology, digital signal processing plays a central role in extracting meaningful information from complex and noisy waveform data recorded by dense seismic networks. This book guides readers from the basics of discrete-time signals to advanced applications in earthquake seismology, emphasizing both conceptual understanding and computational practice. The first chapters introduce core concepts such as discrete-time signals, sampling, interpolation, smoothing, and windowing. Subsequent chapters cover Fourier analysis, convolution and deconvolution, waveform similarity, and digital filtering techniques. The final chapter presents advanced seismological applications, including spectral magnitude estimation, source-time function retrieval, ambient-noise cross-correlation, and site-response analysis using horizontal-to-vertical spectral ratios. Each topic is accompanied by MATLAB implementations and worked examples using synthetic and real seismic data, enabling hands-on learning and reproducible research practice. This book is intended for graduate students, early-career researchers, and practitioners in seismology and related fields who wish to develop both theoretical understanding and practical skills in signal processing. It highlights how modern computational tools transform raw seismic observations into quantitative insights into earthquake sources, wave propagation, and Earth structure.