Xingyi Liu and Keshab K Parhi are researchers from the University of Minnesota. They have developed a new approach to molecular and DNA memristors. This allows for cascading. This new definition of state enables the creation of reservoir computing (RC) models that can process temporal inputs. The cascade connections in a reservoir can change dynamically, reducing the number of memristors needed.
The researchers demonstrated that a DNA RC system can detect seizures. This system consists of DNA memristors and a DNA readout layer. It can also solve time-series prediction tasks. This advancement could have applications in drug delivery, protein therapy, DNA storage, and gene editing.
Introduction to Reservoir Computing with Dynamic Reservoir using Cascaded DNA Memristors
Xingyi Liu and Keshab K Parhi are researchers from the Department of Electrical and Computer Engineering. They are affiliated with the University of Minnesota. They have proposed a new approach to molecular and DNA memristors. In the past, the state of these memristors was defined by two output variables. This made cascading impossible due to differing input and output sizes. The researchers have introduced a different state definition for the molecular and DNA memristors, allowing for cascading.
The Role of Memristors in Reservoir Computing Models
The proposed memristors are used to build reservoir computing (RC) models that can process temporal inputs. An RC system consists of two parts: a reservoir and a readout layer. The reservoir projects the information from the input space into a high-dimensional feature space. The researchers also studied the input-state characteristics of the cascaded memristors and found that they keep the memristive behavior.
The cascade connections in a reservoir can change dynamically. This allows the synthesis of a dynamic reservoir rather than a static one. This reduces the number of memristors significantly compared to a static reservoir. The inputs to the readout layer correspond to one molecule per state. This significantly reduces the number of molecular and DNA strand displacement (DSD) reactions for the readout layer.
Applications of DNA Reservoir Computing Systems
A DNA RC system includes DNA memristors and a DNA readout layer. This system is used to detect seizures from intracranial electroencephalogram (iEEG). The researchers also demonstrated a DNA RC system with three cascaded DNA memristors. This system, combined with a DNA readout layer, can solve the timeseries prediction task.
The proposed approach significantly reduces the number of DNA strand displacement (DSD) reactions. It can do so by three to five times compared to prior approaches.
The Evolution and Future of DNA Memristors
Chua described the original concept of memristors in 1971. Since then, they have been utilized to build numerous machine learning systems. These include in-memory computing systems and reservoir computing (RC) systems. DNA computing has also advanced significantly, with multiple artificial intelligence and machine learning functions achieved using DNA.
The researchers’ work represents a significant step forward in the field. It has potential applications in drug delivery. It can also be useful in protein therapy, DNA storage, and gene editing.
