References: Sampling and Quantization

1. Nyquist–Shannon sampling theorem - Wikipedia - Explains bandlimited sampling, reconstruction, Nyquist rate, spectral replicas, and conditions required to avoid information loss.

2. Aliasing - Wikipedia - Illustrates how inadequate temporal or spatial sampling makes distinct frequencies indistinguishable and motivates anti-alias filtering.

3. Quantization (signal processing) - Wikipedia - Covers quantization levels, error, noise models, uniform and nonuniform quantizers, resolution, and signal-to-quantization-noise ratio.

4. Understanding Digital Signal Processing (3rd Edition) - Richard G. Lyons - Pearson - Lyons’ frequency-folding diagrams and everyday aliases make sampling and spectral replication unusually approachable for beginners.

5. Principles of Digital Communication and Coding - Andrew J. Viterbi and Jim K. Omura - McGraw-Hill - Viterbi and Omura connect quantization and sampling choices to information, distortion, coding, and communication-system performance.

6. Signal Sampling - Engineering LibreTexts - Develops periodic spectral replication and reconstruction conditions from continuous- and discrete-time Fourier representations.

7. The Sampling Theorem - DSP Guide - Gives an intuitive reconstruction-based explanation of Nyquist limits, aliasing, and practical data-conversion decisions.

8. Analog-to-Digital Conversion Activity - Analog Devices - A hands-on treatment of ADC sampling, quantization levels, resolution, error, Nyquist limits, and undersampling.

9. Sigma-Delta ADCs Tutorial - Analog Devices - Explains oversampling, quantization noise, noise shaping, and decimation through frequency-domain diagrams and converter examples.

10. Signals and Systems Lecture Notes - MIT OpenCourseWare - Includes lectures and exercises devoted to sampling, quantization, reconstruction, modulation, and continuous-discrete relationships.