Graph signal recovery using restricted Boltzmann machines

Mohan, Ankith; Nakano, Aiichiro; Ferrara, Emilio

doi:10.1016/j.eswa.2021.115635

Cited by 5 publications

(3 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Different from the traditional neural network, the hidden layer of DBN usually adopts the multiple Restricted Boltzmann Machine (RBM) 6 . In particular, the connection style of hidden layer is flexible, while this letter uses the full connection style.…”

Section: The Proposed Psychology Recognition Methodsmentioning

confidence: 99%

“…Different from the traditional neural network, the hidden layer of DBN usually adopts the multiple Restricted Boltzmann Machine (RBM). 6 In particular, the connection style of hidden layer is flexible, while this letter uses the full connection style. For RBM-based DBN, upon the current-layer training is finished, and the output result is regarded as the input of next-layer RBM; In other words, the whole neural network is trained through the backpropagation of error obtained by Equation (2).…”

Section: The Proposed Psychology Recognition Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Information‐centric networking driven psychology recognition and health conduction of undergraduates

Zhang

2021

Internet Technology Letters

View full text Add to dashboard Cite

It is considerably significant to recognize the psychology of undergraduates especially during the period of COVID‐19 outbreak. This letter proposes an Information‐Centric Networking (ICN) driven psychology recognition and health conduction method based on the active data collection mode, that is, all undergraduates submit their psychology data to manger without protest by the special sensor tool. Meanwhile, the involved undergraduates and the management center construct a large network model. In order to support the mobility of undergraduates, this letter exploits ICN paradigm to help the management and transmission of psychology data. In addition, this management center deploys Deep Belief Network (DBN) to analyze the submitted psychology data. Finally, this letter makes a practical simulation on campus, and the experimental results show that the proposed psychology control method not only has good recognition effect but also contributes to health conduction. To be specific, the proposed method can improve about 2.6% psychology recognition accuracy and decrease about 46.5% psychology recognition time.

show abstract

Section: The Proposed Psychology Recognition Methodsmentioning

confidence: 99%

Section: The Proposed Psychology Recognition Methodsmentioning

confidence: 99%

Information‐centric networking driven psychology recognition and health conduction of undergraduates

Zhang

2021

Internet Technology Letters

View full text Add to dashboard Cite

show abstract

“…As shown in Fig. 5, an RBM usually consists of discrete visible units x ∈ X em and discrete hidden units h (Mohan et al, 2021). The joint probability distribution (x, h) ∼ P(x, h; θ) is defined by the energy function E(x, h; θ) Mohan et al (2021).…”

Section: Tablementioning

confidence: 99%