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Full-Text Articles in Engineering
Brain Inspired Organic Electronic Devices And Systems For Adaptive Signal Processing, Memory, And Learning., Subhadeep Koner
Brain Inspired Organic Electronic Devices And Systems For Adaptive Signal Processing, Memory, And Learning., Subhadeep Koner
Doctoral Dissertations
A new class of electronic device has emerged which bear the potential for low powered brain like adaptive signal processing, memory, and learning. It is a non-linear resistor with memory coined as memristor. A memristor is a two-terminal electrical device which simultaneously changes its resistance (processing information) and store the resistance state pertaining to the applied power (memory). Therefore, it can collocate memory and processing much like our brain synapse which can save time and energy for information processing. Leveraging stored memory, it can thereby help future engineered systems to learn autonomously from past experiences. There has been a growing …
Low-Energy Memristors & High-Nonlinearity Selector For Dense Passive Cross-Bar Arrays, Navnidhi K. Upadhyay
Low-Energy Memristors & High-Nonlinearity Selector For Dense Passive Cross-Bar Arrays, Navnidhi K. Upadhyay
Doctoral Dissertations
Memristor or RRAM (Resistive Random Access Memory) based crossbar array architecture (CBA) is considered a leading contender for the next-generation non-volatile memory (NVM) as well as for future computing paradigms, such as in-memory computing, neuromorphic computing, neural networks, analog computing, reconfigurable computing, etc. Among many other attractive properties, memristors’ simple and dense 3D stackable structure is an essential enabler of these promising applications. However, the simplicity and high density of CBA comes at a price. CBA suffers from the so-called sneak path currents flowing through the unselected cells, which severely affects the read margin, makes CBA more power-hungry, increases the …
Cmos Compatible Memristor Networks For Brain-Inspired Computing, Can Li
Cmos Compatible Memristor Networks For Brain-Inspired Computing, Can Li
Doctoral Dissertations
In the past decades, the computing capability has shown an exponential growth trend, which is observed as Moore’s law. However, this growth speed is slowing down in recent years mostly because the down-scaled size of transistors is approaching their physical limit. On the other hand, recent advances in software, especially in big data analysis and artificial intelligence, call for a break-through in computing hardware. The memristor, or the resistive switching device, is believed to be a potential building block of the future generation of integrated circuits. The underlying mechanism of this device is different from that of complementary metal-oxide-semiconductor (CMOS) …
Analog Signal Processing Solutions And Design Of Memristor-Cmos Analog Co-Processor For Acceleration Of High-Performance Computing Applications, Nihar Athreyas
Analog Signal Processing Solutions And Design Of Memristor-Cmos Analog Co-Processor For Acceleration Of High-Performance Computing Applications, Nihar Athreyas
Doctoral Dissertations
Emerging applications in the field of machine vision, deep learning and scientific simulation require high computational speed and are run on platforms that are size, weight and power constrained. With the transistor scaling coming to an end, existing digital hardware architectures will not be able to meet these ever-increasing demands. Analog computation with its rich set of primitives and inherent parallel architecture can be faster, more efficient and compact for some of these applications. The major contribution of this work is to show that analog processing can be a viable solution to this problem. This is demonstrated in the three …
Memristive Nanodevices And Arrays: Scaling And Novel Applications, Shuang Pi
Memristive Nanodevices And Arrays: Scaling And Novel Applications, Shuang Pi
Doctoral Dissertations
This dissertation addresses the challenges for device scaling and novel application of nanoscale memristive devices and device arrays through demonstrating the first working sub-10 nm memristor array, the first ultra-dense atomic scale working memristor array and the first high performance nanoscale radiofrequency switch based on memristive devices. Nanoimprint lithography is used to generate the sub-10 nm cross-point memristor array. The imprint mold with sub-10 nm features is generated by using wet chemical method to shrink the larger features on a master mold. The imprinting, pattern transfer and metallization process are closely monitored to enforce optimal conditions for sub-1 nm critical …
Three-Dimensional Memristor Integrated Circuits And Applications, Peng Lin
Three-Dimensional Memristor Integrated Circuits And Applications, Peng Lin
Doctoral Dissertations
New computing paradigms are highly demanded in the “Big Data” era to efficiently process, store and extract useful information from overwhelmingly rich amount of data. New computing systems based on large scale memristor circuits emerges as a very promising candidate due to its capability to both store and process information, thus eliminating the von Neumann bottleneck in the conventional complementary metal oxide semiconductor (CMOS) based computers. As the lateral scaling of the device geometry approaching its physical limit, three-dimensional stacking of multiple device layers becomes necessary to further increase the packing density. Moreover, innovations in the 3D circuits design can …