Memristors have provided a new direction of thinking for circuit designers to overcome the limits of scalability and for thinking of building systems beyond Moore’s law. Over the last decade, there has been a significant number of innovations in using memristors for building neural networks through analog computing, in-memory computing, and stochastic computing approaches. The emergence of intelligent integrated circuits is inevitable for the future of integrated circuit applications.

This book provides a collection of talks conducted as part of the IEEE Seasonal School on Circuits and System, having a focus on Intelligence in Chip: Tomorrow of Integrated Circuits. Technical topics discussed in the book include:

• Edge of Chaos Theory Explains Complex Phenomena in Memristor Circuits
• Analog Memristive Computing
• Designing energy efficient neo-cortex system with on-device learning
• Integrated sensors
• Challenges and recent advances in NVM based Neuromorphic Computing ICs
• In-memory Computing (for deep learning)
• Deep learning with Spiking Neural Networks
• Computational Intelligence for Designing Integrated Circuits and Systems
• Neurochip Design, Modeling, and Applications

Memristors have provided a new direction of thinking for circuit designers to overcome the limits of scalability and for thinking of building systems beyond Moore’s law. Over the last decade, there has been a significant number of innovations in using memristors for building neural networks through analog computing, in-memory computing, and stochastic computing approaches. The emergence of intelligent integrated circuits is inevitable for the future of integrated circuit applications.

This book provides a collection of talks conducted as part of the IEEE Seasonal School on Circuits and System, having a focus on Intelligence in Chip: Tomorrow of Integrated Circuits. Technical topics discussed in the book include:

• Edge of Chaos Theory Explains Complex Phenomena in Memristor Circuits
• Analog Memristive Computing
• Designing energy efficient neo-cortex system with on-device learning
• Integrated sensors
• Challenges and recent advances in NVM based Neuromorphic Computing ICs
• In-memory Computing (for deep learning)
• Deep learning with Spiking Neural Networks
• Computational Intelligence for Designing Integrated Circuits and Systems
• Neurochip Design, Modeling, and Applications

Memristors have provided a new direction of thinking for circuit designers to overcome the limits of scalability and for thinking of building systems beyond Moore’s law. Over the last decade, there has been a significant number of innovations in using memristors for building neural networks through analog computing, in-memory computing, and stochastic computing approaches. The emergence of intelligent integrated circuits is inevitable for the future of integrated circuit applications.

This book provides a collection of talks conducted as part of the IEEE Seasonal School on Circuits and System, having a focus on Intelligence in Chip: Tomorrow of Integrated Circuits. Technical topics discussed in the book include:

• Edge of Chaos Theory Explains Complex Phenomena in Memristor Circuits
• Analog Memristive Computing
• Designing energy efficient neo-cortex system with on-device learning
• Integrated sensors
• Challenges and recent advances in NVM based Neuromorphic Computing ICs
• In-memory Computing (for deep learning)
• Deep learning with Spiking Neural Networks
• Computational Intelligence for Designing Integrated Circuits and Systems
• Neurochip Design, Modeling, and Applications