In the era of the Internet and the Internet of Things, display technology has evolved significantly toward full‐scene display and realistic display. Incorporating “intelligence” into displays is a ...crucial technical approach to meet the demands of this development. Traditional display technology relies on distributed hardware systems to achieve intelligent displays but encounters challenges stemming from the physical separation of sensing, processing, and light‐emitting modules. The high energy consumption and data transformation delays limited the development of intelligence display, breaking the physical separation is crucial to overcoming the bottlenecks of intelligence display technology. Inspired by the biological neural system, neuromorphic technology with all‐in‐one features is widely employed across various fields. It proves effective in reducing system power consumption, facilitating frequent data transformation, and enabling cross‐scene integration. Neuromorphic technology shows great potential to overcome display technology bottlenecks, realizing the full‐scene display and realistic display with high efficiency and low power consumption. This review offers a comprehensive summary of recent advancements in the application of neuromorphic technology in displays, with a focus on interoperability. This work delves into its state‐of‐the‐art designs and potential future developments aimed at revolutionizing display technology.
Display technology evolves significantly toward the full‐scene display and realistic display. To overcome the bottlenecks caused by the physical separation of sensing, processing, and light‐emitting modules, a discussion of how the neuromorphic technology is to be applied in the display is presented. In addition, neuromorphic display, a novel technology for intelligence display, is also discussed.
This paper presents a test bed demonstration of NeuroEdge computing for face recognition using a novel neuromorphic chip-NM500. First, a general description and important specifications of the NM500 ...are presented. Second, a face recognition test-bed case study is used to demonstrate the efficacy and efficiency of the chip. Neuromorphic technology offers scalability and consistent recognition time, which is required by real-time networked systems, and presents a considerable advantage for real-time computations, making them virtually independent of the dataset size. In this study, intelligent edge computing technology was introduced using NeuroEdge. The performance was verified using a face recognition test. The results demonstrated that using neuromorphic technology, such as the NM500 chip, saves the time needed for training systems and does not impose the burden of requiring many datasets for effective training.
Neuromorphic computing is an emerging technology that describes the biological neural systems and implementation of its electrical model in complementary metal-oxide-semiconductor (CMOS) VLSI system. ...Three dimensional (3D) integration can be applied in hardware implementation of neuromorphic computing that provides high device interconnection density using fast and energy efficient links with excellent distribution and communication among the neuron layers. In this work, we studied the necessities of neuromorphic computing based on 3D integration technology, design challenges, and a possible solution to overcome the effect of huge parallelism of well-connected synaptic system. Using the force directed optimization algorithm, an optimal interconnect array pattern is identified for a proposed structure that could mitigate significant amount of crosstalk. For the analysis of crosstalk, an electrical model of the optimal array structure is proposed and it has been validated by comparing its simulation results with those extracted from commercial tools. This work can be used as a basis study for successful implementation of next generation 3D neuromorphic computation for high performance application.
A silicon synapse circuit designed in 180 nm CMOS technology is presented in conjunction with relaxation-based neuronal oscillators. The synapse allows excitatory as well as inhibitory coupling of ...artificial spiking neurons. The coupling weights are determined by resistors, for which integration as memristive devices is targeted. Simulation results for one excitatory and one inhibitory neuron connected to a third summing neuron confirm that the summing neuron firing rate is reduced (inhibited) or increased (excited) respectively in accordance with relative coupling strengths and firing rates.
This paper presents prospect and challenges of using state-of-the-art memory technologies in neuro-inspired computing. As it has become critical to move beyond the Von-Neumann architecture, emulation ...of biological system has been sought after. In this paper, characteristics of a desired synaptic device required for constructing neural network are examined to highlight what functionalities of synapses can be emulated with new non-volatile memory (NVM) devices, what the basic requirements are to realize artificial inorganic neurons and synapses, and which material and device structures can be used for this purpose.
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