Razavi B. Analysis and Design of Data Converters 2025

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Razavi B. Analysis and Design of Data Converters 2025

Textbook in PDF format Master the art of data converter design with this definitive textbook, a detailed and accessible introduction ideal for students and practicing engineers. Razavi's distinctive and intuitive pedagogical approach, building up from elementary components to complex systems. Step-by-step transistor-level designs and simulations offer a practical hands-on understanding of key design concepts. Comprehensive coverage of essential topics including sampling circuits, comparator design, digital-to-analog converters, flash topologies, SAR and pipelined architectures, time-interleaved converters, and oversampling systems. Over 250 examples pose thought-provoking questions, reinforcing core concepts and helping students develop confidence. Over 350 end-of-chapter homework problems to test student understanding, with solutions available for course instructors. Developed by leading author Behzad Razavi, and addressing all the principles and design concepts essential to today's engineers, this is the ideal text for senior undergraduate and graduate-level students and professional engineers who aspire to excel in data converter analysis and design. Data converters are an integral part of most electronic systems and play a key role in communications and signal processing. Examples include wireless and wireline transceivers, imaging applications, audio and video processing, and instrumentation. Despite decades of development, data converters continue to present new challenges as we push for higher speeds and lower power consumption. We begin with fundamental building blocks such as sampling circuits, comparators, and digital-to-analog converters. Next, we deal with Nyquist-rate analog-to-digital converters (ADCs), focusing on flash, successive-approximation, pipelined, and interleaved architectures. We then turn to oversampling converters, introduce the concept of noise shaping, study the basic design of such architectures, and analyze their imperfections. We also present more advanced topics such as cascaded topologies and data-weighted averaging