Two Memristors-Based XOR Logic Demonstrated With Encryption/Decryption

Song, Yujie; Wu, Qiwen; Wang, Xinsheng; Wang, Chengxu; Miao, Xiangshui

doi:10.1109/led.2021.3102678

Cited by 21 publications

(8 citation statements)

References 23 publications

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“…In contrast with LIM based on memristors, it has been calculated that the energy consumption required to calculate XOR logic is no more than 1 pJ, which is competitive. [ 39 ] Compared with CMOS circuits, the area of the crossbar array can be significantly reduced, and the consumption of static power and data handling can be eliminated (Table S2 , Supporting Information). It is suitable for the application scenario of edge processors, due to the fact that power consumption is a very important consideration in the edge computing and design.…”

Section: Resultsmentioning

confidence: 99%

Reconfigurable and Efficient Implementation of 16 Boolean Logics and Full‐Adder Functions with Memristor Crossbar for Beyond von Neumann In‐Memory Computing

Song

Wang

et al. 2022

Advanced Science

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The rise of emerging technologies such as Big Data, the Internet of Things, and artificial intelligence, which requires efficient power schemes, is driving brainstorming in data computing and storage technologies. In this study, merely relying on the fundamental structure of two memristors and a resistor, arbitrary Boolean logic can be reconfigured and calculated in two steps, while no additional voltage sources are needed beyond "±V P " and 0, and all state reversals are based on memristor set switching. Utilizing the proposed logic scheme in an elegant form of unity structure and minimum cost, the implementation of a 1-bit adder is demonstrated economically, and a promising circuit scheme for the N-bit adder is exhibited. Some critical issues including the crosstalk problem, energy consumption, and peripheral circuits are further simulated and discussed. Compared with existing works on memristive logic, such methods support building a memristor-based digital in-memory calculation system with high functional reconfigurability, simple voltage sources, and low power and area consumption.

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Section: Resultsmentioning

confidence: 99%

Reconfigurable and Efficient Implementation of 16 Boolean Logics and Full‐Adder Functions with Memristor Crossbar for Beyond von Neumann In‐Memory Computing

Song

Wang

et al. 2022

Advanced Science

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“…Encryption and decryption of information is another way to ensure information security. Song et al proposed an optimized XOR logic gate based on TiN/Ti/HfO x /TiN memristor [ 208 ]. The encryption and decryption based on the XOR circuit consisting of two memristors was verified by successfully performing parallel electrical tests [ 208 ].…”

Section: Applicationsmentioning

confidence: 99%

A review of memristor: material and structure design, device performance, applications and prospects

Xiao

Jiang

Chen

et al. 2023

Science and Technology of Advanced Materials

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With the booming growth of artificial intelligence (AI), the traditional von Neumann computing architecture based on complementary metal oxide semiconductor devices are facing memory wall and power wall. Memristor based in-memory computing can potentially overcome the current bottleneck of computer and achieve hardware breakthrough. In this review, the recent progress of memory devices in material and structure design, device performance and applications are summarized. Various resistive switching materials, including electrodes, binary oxides, perovskites, organics, and two-dimensional materials, are presented and their role in the memristor are discussed. Subsequently, the construction of shaped electrodes, the design of functional layer and other factors influencing the device performance are analyzed. We focus on the modulation of the resistances and the effective methods to enhance the performance. Furthermore, synaptic plasticity, optical-electrical properties, the fashionable applications in logic operation and analog calculation are introduced. Finally, some critical issues such as the resistive switching mechanism, multi-sensory fusion, system-level optimization are discussed.

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“…Recently, researchers are making efforts to drive biological neural networks and map with memristive neuromorphic models to customize AI-based Robots [7], [8], [9]. Similarly, memristive neuromorphic models have been applied in most computing acceleration designs [10], [11], [12].…”

Section: A Backgroundmentioning

confidence: 99%

ASM-ROBOT: A Cyber-Physical Home Automation Controller with Memristive Reconfigurable State Machine

Okafor¹,

Longe²

2022

IJACSA

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In the next 5 to 10 years, digital Artificial Intelligence with Machine Circuit Learning Algorithms (MCLA) will become the mainstream in complex automated robots. Its power concerns, ethical perspectives, including the issues of digital sensing, actuation, mobility, efficient processcomputation, and wireless communication will require advanced neuromorphic process variable controls. Existing home automated robots lack memristic associative memory. This work presents Cyber-Physical Home Automation System (CPHAS) using Memristive Reconfigurable Algorithmic State Machine (MRASM) chart. A process control architecture that supports Concurrent Wireless Data Streams and Power-Transfer (CWDSPT) is developed. Unlike legacy systems with powersplitting (PS) and time-switching (TS) controls, the MRASM-ROBOT explores granular wireless signal controls through unmodulated high-power continuous wave (CW). This transmits infinite process variables using Orthogonal Space-Time Block Code (OSTBC) for interference reduction. The CWDSPT transmitter and receiver circuit design for signal processing are implemented with complexity noise-error reduction during telemetry data decoding. Received signals are error-buffered while gathering control variables' status.Transceiver Memristive neuromorphic circuits are introduced for computational acceleration in the design. Hardware circuit design is tested for system reliability considering the derived schematic models for all process variables. Under small range space diversity, the system demonstrated significant memory stabilization at the synchronous iteration of the synaptic circuitry.

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Two Memristors-Based XOR Logic Demonstrated With Encryption/Decryption

Cited by 21 publications

References 23 publications

Reconfigurable and Efficient Implementation of 16 Boolean Logics and Full‐Adder Functions with Memristor Crossbar for Beyond von Neumann In‐Memory Computing

Reconfigurable and Efficient Implementation of 16 Boolean Logics and Full‐Adder Functions with Memristor Crossbar for Beyond von Neumann In‐Memory Computing

A review of memristor: material and structure design, device performance, applications and prospects

ASM-ROBOT: A Cyber-Physical Home Automation Controller with Memristive Reconfigurable State Machine

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