This book is a single-source guide to nonlinearity and nonlinear techniques in energy harvesting, with a focus on vibration energy harvesters for micro and nanoscale applications. The authors demonstrate that whereas nonlinearity was avoided as an undesirable phenomenon in early energy harvesters, now it can be used as an essential part of these systems. Readers will benefit from an overview of nonlinear techniques and applications, as well as deeper insight into methods of analysis and modeling of energy harvesters, employing different nonlinearities. The role of nonlinearity due to different aspects of an energy harvester is discussed, including nonlinearity due to mechanical-to-electrical conversion, nonlinearity due to conditioning electronic circuits, nonlinearity due to novel materials (e.g., graphene), etc. Coverage includes tutorial introductions to MEMS and NEMS technology, as well as a wide range of applications, such as nonlinear oscillators and transducers for energy harvesters and electronic conditioning circuits for effective energy processing.

This book deals with energy delivery challenges of the power processing unit of modern computer microprocessors. It describes in detail the consequences of current trends in miniaturization and clock frequency increase, upon the power delivery unit, referred to as voltage regulator. This is an invaluable reference for anybody needing to understand the key performance limitations and opportunities for improvement, from both a circuit and systems perspective, of state-of-the-art power solutions for next generation CPUs.

This book describes the structured design and optimization of efficient, energy processing integrated circuits. The approach is multidisciplinary, covering the monolithic integration of IC design techniques, power electronics and control theory. In particular, this book enables readers to conceive, synthesize, design and implement integrated circuits with high-density high-efficiency on-chip switching power regulators. Topics covered encompass the structured design of the on-chip power supply, efficiency optimization, IC-compatible power inductors and capacitors, power MOSFET switches and efficient switch drivers in standard CMOS technologies.

This book addresses the need for models and techniques to predict stability boundaries, given trends toward miniaturization of switching power supplies in battery-operated portable devices, which lead to the exhibition of fast-scale chaotic instabilities. The authors describe a method to predict stability boundaries from a design-oriented perspective, which captures the effect of the different parameters of the system upon the particular boundary. Unlike previous methods involving complex analysis based on the discrete-time mathematical model, the method introduced here allows for prediction of the overall stability boundaries within the complete design space and is based upon a simple design-oriented index."

This book deals with energy delivery challenges of the power processing unit of modern computer microprocessors. It describes in detail the consequences of current trends in miniaturization and clock frequency increase, upon the power delivery unit, referred to as voltage regulator. This is an invaluable reference for anybody needing to understand the key performance limitations and opportunities for improvement, from both a circuit and systems perspective, of state-of-the-art power solutions for next generation CPUs.

This book describes the structured design and optimization of efficient, energy processing integrated circuits. The approach is multidisciplinary, covering the monolithic integration of IC design techniques, power electronics and control theory. In particular, this book enables readers to conceive, synthesize, design and implement integrated circuits with high-density high-efficiency on-chip switching power regulators. Topics covered encompass the structured design of the on-chip power supply, efficiency optimization, IC-compatible power inductors and capacitors, power MOSFET switches and efficient switch drivers in standard CMOS technologies.

This book addresses the need for models and techniques to predict stability boundaries, given trends toward miniaturization of switching power supplies in battery-operated portable devices, which lead to the exhibition of fast-scale chaotic instabilities. The authors describe a method to predict stability boundaries from a design-oriented perspective, which captures the effect of the different parameters of the system upon the particular boundary. Unlike previous methods involving complex analysis based on the discrete-time mathematical model, the method introduced here allows for prediction of the overall stability boundaries within the complete design space and is based upon a simple design-oriented index.

This book is a single-source guide to nonlinearity and nonlinear techniques in energy harvesting, with a focus on vibration energy harvesters for micro and nanoscale applications. The authors demonstrate that whereas nonlinearity was avoided as an undesirable phenomenon in early energy harvesters, now it can be used as an essential part of these systems. Readers will benefit from an overview of nonlinear techniques and applications, as well as deeper insight into methods of analysis and modeling of energy harvesters, employing different nonlinearities. The role of nonlinearity due to different aspects of an energy harvester is discussed, including nonlinearity due to mechanical-to-electrical conversion, nonlinearity due to conditioning electronic circuits, nonlinearity due to novel materials (e.g., graphene), etc. Coverage includes tutorial introductions to MEMS and NEMS technology, as well as a wide range of applications, such as nonlinear oscillators and transducers for energy harvesters and electronic conditioning circuits for effective energy processing.

The field of AI is not new to researchers, as its foundations were established in the 1950s. After many decades of inattention, there has been a dramatic resurgence of interest in AI, fueled by a confluence of several factors. The benefits of decades of Dennard scaling and Moore's law miniaturization, coupled with the rise of highly distributed processing, have led to massively parallel systems well suited for handling big data. The widespread availability of big data, necessary for training AI algorithms, is another important factor. Finally, the greatly increased compute power and memory bandwidths have enabled deeper networks and new algorithms capable of accuracy rivaling that of human perception. Already AI has shown success in many diverse areas, including finance (portfolio management, investment strategies), marketing, health care, transportation, gaming, defense, robotics, computer vision, education, search engines, online assistants, image/facial recognition, anomaly detection, spam filtering, online customer service, biometric sensors, and predictive maintenance, to name a few. Despite these remarkable advances, the human brain is still superior in many ways - including, notably, energy efficiency and one-shot learning - giving researchers new areas to explore. In summary, AI research and applications will continue with vigor in software, algorithms, and hardware accelerators. These exciting developments have also brought new questions of ethics and privacy, areas which must be studied in tandem with technological advances. To continue the success story of AI, the AI Compute symposium was launched with the sponsorship of IBM, IEEE CAS and EDS for the first time. The aim of this publication is to compile all the materials presented by the renowned speakers in the symposium into a book format, serving as a learning tool for the audience. This book contains two broad topics: general AI advances (chapters 1-5) and neuromorphic computing directions (chapters 6-9). Technical topics discussed in the book include: 1. Research Directions in AI algorithms and systems 2. An ARM perspective on hardware requirements and challenges for AI 3. The new Era of AI hardware 4. AI and the Opportunity for Unconventional Computing Platforms 5. Thermodynamic Computing 6. Brain-like cognitive engineering system 7. BRAINWAY and Nano - Abacus architecture: Brain-inspired Cognitive Computing using Energy Efficient Physical Computational Structures, Algorithms and Architecture Co-Design 8. Applying Lessons from Nature for Today's Computing Challenges 9. Emerging Memories - RRAM Fabric for Neuromorphic Computing Applications