K Srinivasa Rao – författare

MACHINE LEARNING TECHNIQUES FOR VLSI CHIP DESIGN This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, the efficient hardware of machine learning applications with FPGA or CMOS circuits, and many other aspects and applications of machine learning techniques for VLSI chip design. Artificial intelligence (AI) and machine learning (ML) have, or will have, an impact on almost every aspect of our lives and every device that we own. AI has benefitted every industry in terms of computational speeds, accurate decision prediction, efficient machine learning (ML), and deep learning (DL) algorithms. The VLSI industry uses the electronic design automation tool (EDA), and the integration with ML helps in reducing design time and cost of production. Finding defects, bugs, and hardware Trojans in the design with ML or DL can save losses during production. Constraints to ML-DL arise when having to deal with a large set of training datasets. This book covers the learning algorithm for floor planning, routing, mask fabrication, and implementation of the computational architecture for ML-DL. The future aspect of the ML-DL algorithm is to be available in the format of an integrated circuit (IC). A user can upgrade to the new algorithm by replacing an IC. This new book mainly deals with the adaption of computation blocks like hardware accelerators and novel nano-material for them based upon their application and to create a smart solution. This exciting new volume is an invaluable reference for beginners as well as engineers, scientists, researchers, and other professionals working in the area of VLSI architecture development.

NANODEVICES FOR INTEGRATED CIRCUIT DESIGN Nanodevices are an integral part of many of the technologies that we use every day. It is a constantly changing and evolving area, with new materials, processes, and applications coming online almost daily. Increasing demand for smart and intelligent devices in human life with better sensing, communication and signal processing is increasingly pushing researchers and designers towards future design challenges based upon internet-of-things (IoT) applications. Several types of research have been done at the level of solid-state devices, circuits, and materials to optimize system performance with low power consumption. For suitable IoT-based systems, there are some key areas, such as the design of energy storage devices, energy harvesters, novel low power high-speed devices, and circuits. Uses of new materials for different purposes, such as semiconductors, metals, and insulators in different parts of devices, circuits, and energy sources, also play a significant role in smart applications of such systems. Emerging techniques like machine learning and artificial intelligence are also becoming a part of the latest developments in an electronic device and circuit design. This groundbreaking new book will, among other things, aid developing countries in updating their semiconductor industries in terms of IC design and manufacturing to avoid dependency on other countries. Likewise, as an introduction to the area for the new-hire or student, and as a reference for the veteran engineer in the field, it will be helpful for more developed countries in their pursuit of better IC design. It is a must have for any engineer, scientist, or other industry professional working in this area.

With its in-depth exploration of the close connection between microelectronics, AI, and VLSI technology, this book offers valuable insights into the cutting-edge techniques and tools used in VLSI design automation, making it an essential resource for anyone seeking to stay ahead in the rapidly evolving field of VLSI design. Very large-scale integration (VLSI) is the inter-disciplinary science of utilizing advanced semiconductor technology to create various functions of computer system. This book addresses the close link of microelectronics and artificial intelligence (AI). By combining VLSI technology, a very powerful computer architecture confinement is possible. To overcome problems at different design stages, researchers introduced artificial intelligent (AI) techniques in VLSI design automation. AI techniques, such as knowledge-based and expert systems, first try to define the problem and then choose the best solution from the domain of possible solutions. These days, several CAD technologies, such as Synopsys and Mentor Graphics, are specifically created to increase the automation of VLSI design. When a task is completed using the appropriate tool, each stage of the task design produces outcomes that are more productive than typical. However, combining all of these tools into a single package offer has drawbacks. We can’t really use every outlook without sacrificing the efficiency and usefulness of our output. The researchers decided to include AI approaches into VLSI design automation in order to get around these obstacles. AI is one of the fastest growing tools in the world of technology and innovation that helps to make computers more reliable and easy to use. Artificial Intelligence in VLSI design has provided high-end and more feasible solutions to the difficulties faced by the VLSI industry. Physical design, RTL design, STA, etc. are some of the most in-demand courses to enter the VLSI industry. These courses help develop a better understanding of the many tools like Synopsis. With each new dawn, artificial intelligence in VLSI design is continually evolving, and new opportunities are being investigated.

Field Effect Transistors is an essential read for anyone interested in the future of electronics, as it provides a comprehensive yet accessible exploration of innovative semiconductor devices and their applications, making it a perfect resource for both beginners and seasoned professionals in the field. Miniaturization has become the slogan of the electronics industry. Field Effect Transistors serves as a short encyclopedia for young minds looking for solutions in the miniaturization of semiconductor devices. It explores the characteristics, novel materials used, modifications in device structure, and advancements in model FET devices. Though many devices following Moore’s Law have been proposed and designed, a complete history of the existing and proposed semiconductor devices is not available. This book focuses on developments and research in emerging semiconductor FET devices and their applications, providing unique coverage of topics covering recent advancements and novel concepts in the field of miniaturized semiconductor devices. Field Effect Transistors is an easy-to-understand guide, making it excellent for those who are new to the subject, giving insight and analysis of recent developments and developed semiconductor device structures along with their applications.

Sharing valuable insights into the many stages of Ramanujan’s life, this book provides glimpses into his prolific research on highly composite numbers, partitions, continued fractions, mock theta functions, arithmetic, and hypergeometric functions which led the author to discover a new summation theorem.

Sharing valuable insights into the many stages of Ramanujan’s life, this book provides glimpses into his prolific research on highly composite numbers, partitions, continued fractions, mock theta functions, arithmetic, and hypergeometric functions which led the author to discover a new summation theorem.

The book introduces the research significance of biomedical instrumentation and discusses micro-fabrication techniques utilized for biomedical devices. This book primarily focuses on the reader enlightenment on MEMS medical devices by introducing all the diagnostic devices and treatment tools at one place.