Memistor

About: Memistor is a research topic. Over the lifetime, 608 publications have been published within this topic receiving 34905 citations.

Nonvolatile Logic‐in‐Memory Computing based on Solution‐Processed CuI Memristor

Abstract: Memristors are intensively studied as being regarded as the critical components to realize the in‐memory computing paradigm. A novel electrochemical metallization memristor based on solution‐processed Pt/CuI/Cu structure is proposed and demonstrated in this work, with a high resistance switching ratio of 1.53 × 107. Owing to the efficient drift paths provided by Cu vacancies for Cu cations in CuI, very small operating voltages (Vset = 0.64 V and Vreset = −0.19 V) are characterized, contributing to ultralow standby power consumption of 9 fW and per set transition of 8.73 µW. Using CuI memristor arrays, a set of Boolean logic operations and a half‐adder are implemented. Moreover, by building the model for a 75 × 48 one‐transistor‐one‐memristor array, the feasibility of hardware encryption and decryption for images is verified. All these demonstrate that solution‐processed CuI memristors possess great potential in constructing energy‐efficient logic‐in‐memory computing architectures.

Imply logic based on TiO 2 memristor model for computational circuits

Abstract: Memristor's main attribute is a varying resistance with the memory, Hence the name memory and resistor. So far the primary applications explored for memristors where in the field of memory arrays and neuromorphic networks. This paper explores the utilization of logic with memristors. Due to the fact that the field is in its early stages of research, various types of memristor models exist, and there is no wide consensus as to which one best describes the physical properties. In order for the research to relevant in any case, hybrid memristor model is considered. Logic family of memristor is considered. memristors as logic within memory, memristors as computation units. The paper also include the preferred logic family for each type of memristor, and advantages and disadvantages of each logic family.

Research on a chaotic circuit based on an active TiO 2 memristor

Abstract: The memristor is the fourth fundamental circuit element besides the resistor, inductor and capacitor. As a two-terminal nonlinear resistor, the memristor has a broad application prospect. In this paper, a negative memconductance expression of a flux-controlled memristor is derived from the relationship between voltage and current for the Hewlett-Packard memristor. By replacing Chua's diode with the active flux-controlled TiO 2 memristor, a chaotic circuit is obtained. By means of the conventional dynamic analysis method, dynamic behaviors of the chaotic circuit are investigated. Software simulation and theoretical analysis all indicate that this active memristor-based chaotic circuit has more complex behaviors. Furthermore, the integrated circuit experiment on the digital signal processor chip of this circuit was also realized.

Memristor devices for use in neuromorphic systems

Abstract: This paper describes the fabrication and characterization process used to develop memristors that are strong candidates for use in neuromorphic systems. A common approach for the development of memristor-based neuromorphic circuits is to store synaptic weight values within memristors as resistance values. This requires use of the continuous resistance range available in the memristors to store the weight matrix produced by a learning algorithm. More specifically, these devices will be used in systems that implement supervised learning algorithms such as single and multilayer perceptrons. It is important to be able to iteratively program a target resistance through a number of feedback controlled voltage pulses as opposed to abruptly switching the device between two binary states. This paper shows how TiO 2 memristor devices placed in a crossbar arrangement are capable of implementing Boolean logic functions using a perceptron algorithm. Resistances within a memristor crossbar can be tuned and reconfigured so that a neuron circuit based on this crossbar can represent multiple different functions.