JOURNALS

• Slow manifolds within network dynamics encode working memory efficiently and robustly. "PLoS Computational Biology - 2021"

  Elham Ghazizadeh , ShiNung Ching

• Creating functionally favorable neural dynamics by maximizing information capacity. "Neurocomputing - 2020"

  Elham Ghazizadeh , ShiNung Ching

• An enhanced two‐phase SVM algorithm for cooperative spectrum sensing in Cognitive Radio networks."International Journal of Communication Systems - 2018"

  Elham Ghazizadeh, Dariush Abbasi Moghadam, Hossein Nezamabadipour

• Game theoretic spectrum allocation in femtocell networks for smart electric distribution grids. "Energies - 2018"

  Ali Mohammadi, Mohammad Javad Dehghani, Elham Ghazizadeh

CONFERENCES

• Diverse Dynamical Mechanisms Underlying Working Memory Function in Recurrent Networks. "NeurIPS Workshop - 2020"

  Elham Ghazizadeh, ShiNung Ching

• Defining information-based functional objectives for neurostimulation and control. "Amecrican Control Conference (ACC)- 2019"

  Elham Ghazizadeh, Peng Yi, ShiNung Ching

• A PSO-based weighting method to enhance machine learning techniques for cooperative spectrum sensing in Cognitive Radio networks. "Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) -2016"

  Elham Ghazizadeh, Bahareh Nikpour, Dariush Abbasi Moghadam, Hossein Nezamabadi-pour

ABSTRACTS

• Slow manifolds and output attractors as the substrate for working memory in recurrent networks. I presented it in "Computational and Syetem Neuroscience (Cosyne) - 2020"

  Elham Ghazizadeh, Lawrence Snyder, ShiNung Ching

• Google Scholar