Initiative, Immersive Human–Computer Interactions: Software-Defined Memristive Neural Networks for Nonlinear Heterogeneous Scheme in Internet of Brains

Metaverse is an initiative, an immersive virtual-reality (VR) digital space that installs to the next-generation Internet for a platform of network human–computer interaction mode. As the access point number of routing/switching process in a nonlinear heterogeneous scheme (NLHS) is increased, the original method for the word, voice, or image transmission cannot conform to the node and link delay needs of multilead electroencephalogram, and multimedia audio/video operating in brain–computer interface or VR terminal. The parallelization and distribution of data streams with routing/switching capability were not only embed in software-defined network but also play a critical role in software-defined radio. The purpose of this manuscript is to enable the Metaverse to get an initiative control and immersive perceptual abilities, we introduce an NLHS to make a novel initiative, immersive human–computer interactions: software-defined memristive neural networks (MNNs). In the link/network layer, we use the function of software-defined approach in control of a threshold during the early high-speed switching fabric in EEG input or audio/video output. However, the multiple control or perceptual data streams of our thought and sense in conventional routing nodes remain a poorly serial running state all the time. Here, we design a large-scale switch parallelization of memristor-based FPGA system on a basis of previous NLHS for the designing of a routing node in MNN. To conclude, our results verify a high performance in the novel human–computer interaction with multilead/multimedia information.