no code implementations • 8 Jan 2023 • Mohammad Esmaeili, Aria Nosratinia
We analyze the conditions for exact recovery when these auxiliary latent variables are unknown, representing unknown nuisance parameters or model mismatch.
no code implementations • 13 Sep 2021 • Reza Bagherian Azhiri, Mohammad Esmaeili, Mehrdad Nourani
Real-time classification of Electromyography signals is the most challenging part of controlling a prosthetic hand.
no code implementations • 1 Jul 2021 • Reza Bagherian Azhiri, Mohammad Esmaeili, Mehrdad Nourani
The experimental results illustrate that the proposed method enhances the accuracy of real-time classification of EMG signals up to $95. 5\%$ for $800$ msec signal length.
no code implementations • 19 Jun 2021 • Reza Bagherian Azhiri, Mohammad Esmaeili, Mohsen Jafarzadeh, Mehrdad Nourani
Electromyography is a promising approach to the gesture recognition of humans if an efficient classifier with high accuracy is available.
1 code implementation • 6 May 2021 • Mohammad Esmaeili, Hussein Metwaly Saad, Aria Nosratinia
SDP is an efficient solution for standard community detection on graphs.
no code implementations • 8 Feb 2021 • Mohammad Esmaeili, Aria Nosratinia
In community detection, the exact recovery of communities (clusters) has been mainly investigated under the general stochastic block model with edges drawn from Bernoulli distributions.
1 code implementation • 29 Sep 2020 • Mohammad Esmaeili, Aria Nosratinia
Another contribution of this paper is relevant to non-graph observations (independent side information) that exists beside a graph realization in many applications.