Digital Signal Processing By Sanjay Sharma -

If you’re struggling with your DSP course, buy this book—not as your only reference, but as your . Work through every example in Chapters 4 (Z-transform), 6 (DFT/FFT), and 8 (IIR filter design). By the end, the fog will lift.

But learning DSP is notoriously tough. The dual hurdles—complex mathematics (convolution, Z-transforms, FFT) and abstract conceptual leaps—trip up many students.

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Why Sanjay Sharma’s ‘Digital Signal Processing’ Remains a Core Text for Engineers

Recommended pairing: Sharma’s book + a Jupyter notebook with numpy.fft and scipy.signal . Theory + code = real understanding. If you’re struggling with your DSP course, buy

This is the book’s killer feature. For every major algorithm—convolution, filter design, FFT butterfly diagrams—Sharma provides dozens of fully worked numericals . You aren’t just told what a discrete Fourier transform is; you’re walked through 10 variations of computing it. For struggling students, this repetition is invaluable.

If you’ve studied electronics or communication engineering, you know that is where abstract math meets real-world utility. It’s the science behind everything from noise-canceling headphones to 5G modems and medical imaging. But learning DSP is notoriously tough

That’s where has earned its reputation. While not as globally famous as Oppenheim or Proakis, Sharma’s text is widely used across Indian and Asian technical universities for a very clear reason: it bridges the gap between theory and application without drowning the reader in proofs. What Makes This Book Stand Out? 1. Exam-Focused Without Being Superficial Unlike many Western textbooks that prioritize theoretical depth, Sharma structures content to align with standard university syllabi (e.g., RTU, AKTU, PTU). Each chapter explicitly targets common exam problems: finding the Z-transform of a sequence, designing an IIR filter via bilinear transformation, or computing the DFT.