The development of flexible and conformable devices, whose performance can be
maintained while being continuously deformed, provides a significant step toward the …

The quest to imbue machines with intelligence akin to that of humans, through the
development of adaptable neuromorphic devices and the creation of artificial neural …

Neuromorphic electronics have great potential in the emulation of the sensory, cognitive, self-
learning, and actuating functions of robots. While typically implemented in rigid silicon …

This work proposes a novel modeling approach for analog organic circuits using very simple
to customize circuit topology and parameters of individual p-and n-type organic field effect …

Recent advances in science and technology have enabled a promising future for wearable
devices with the ability to seamlessly interact with their users. The next generation of …

Artificial intelligence (AI) and deep learning rely on artificial neural networks that are typically
executed on conventional von Neumann architecture-based computers, mostly operating in …

Memristive devices offer essential properties to become a part of the next-generation
computing systems based on neuromorphic principles. Organic memristive devices exhibit a …

Accumulated detailed knowledge about the neuronal activities in human brains has brought
more attention to bio-inspired spiking neural networks (SNNs). In contrast to non-spiking …

This paper presents techniques to accelerate deep neural networks in an FPGA-based
System-On-Chip (SOC). This paper also summarizes the latest advancements in deep …