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Digital Signal Processing (DSP) is the study and application of techniques to analyze, modify, and synthesize signals in digital form. It involves converting real-world analog signals—such as sound, images, and sensor data—into digital data, processing them with mathematical algorithms, and converting the results back for practical use. This discipline is fundamental in numerous fields, including telecommunications, audio and video processing, medical imaging, and control systems.This course/book provides a thorough understanding of key DSP concepts such as discrete-time signals, Fourier and Z-transforms, sampling theory, and digital filter design. Emphasis is placed on both theoretical foundations and practical implementations, often using tools like MATLAB or Python to simulate and solve real-world signal processing problems. Ideal for engineering students, researchers, and professionals, this resource prepares learners to design and implement DSP systems across diverse technological domains.