most citedProduct Reservoir Computing: Time-Series Computation with Multiplicative Neurons

4 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.NE2016

Memory and Information Processing in Recurrent Neural Networks

Alireza Goudarzi, Sarah Marzen, Peter Banda +3

Recurrent neural networks (RNN) are simple dynamical systems whose computational power has been attributed to their short-term memory. Short-term memory of RNNs has been previously…

cs.ET2015

Computational Capacity and Energy Consumption of Complex Resistive Switch Networks

Jens Burger, Alireza Goudarzi, Darko Stefanovic +1

Resistive switches are a class of emerging nanoelectronics devices that exhibit a wide variety of switching characteristics closely resembling behaviors of biological synapses. Ass…

cs.ET20151 cited

Hierarchical Composition of Memristive Networks for Real-Time Computing

Jens Bürger, Alireza Goudarzi, Darko Stefanovic +1

Advances in materials science have led to physical instantiations of self-assembled networks of memristive devices and demonstrations of their computational capability through rese…

cs.NE20151 cited

Exploring Transfer Function Nonlinearity in Echo State Networks

Alireza Goudarzi, Alireza Shabani, Darko Stefanovic

Supralinear and sublinear pre-synaptic and dendritic integration is considered to be responsible for nonlinear computation power of biological neurons, emphasizing the role of nonl…

cs.NE20154 cited

Product Reservoir Computing: Time-Series Computation with Multiplicative Neurons

Alireza Goudarzi, Alireza Shabani, Darko Stefanovic

Echo state networks (ESN), a type of reservoir computing (RC) architecture, are efficient and accurate artificial neural systems for time series processing and learning. An ESN con…