Graduate School of Systemic Neurosciences GSN-LMU
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Mohsen Firouzi

Mohsen Firouzi

Ph.D. student

Contact

Institute of Automatic Control Engineering – TUM
CCRL-II, NST, 5001
Karlstr. 45
D-80333, Munich

Phone: +49 (0)89 / 289-26906

Website: https://www.nst.ei.tum.de/team/mohsen-firouzi/

Further Information

Nationality: Iranian

Topic of Thesis: Brain Cortical Distributed Computing, An approach to Computing (Sensor Fusion in Cortical Circuits)

Supervisor: Prof. Dr. Jörg Conradt, Prof. Dr. Stefan Glasauer

Publication(s):

Firouzi M, Shouraki SB and Esmaili Paeen Afrakuti I. (Accepted) Pattern Analysis by Active Learning Method Classifier. Journal of Intelligent & Fuzzy Systems 26(1): 49-62, IOS press, Netherland.

Ghazanfari A, Mokhtari H and Firouzi M. (2012) Simple Voltage Balancing Approach for CHB Multilevel Inverter Considering Low Harmonic Content Based on a Hybrid Optimal Modulation Strategy. IEEE Transactions on Power Delivery 27(4): 2150 - 2158.

Zakerzadeh MR, Firouzi M, Sayyaadi H and Shouraki SB. (2011) Hysteresis Nonlinearity Identification Using New Preisach Based Artificial Neural Network Approach. Journal of Applied Mathematics, Special Issue on Qualitative Analysis of Dynamic Activity Patterns in Neural Networks, March 2011.

Firouzi M, Shouraki SB and Rostami MGh. (2011) Spiking Neural Network Ink Drop Spread, Spike-IDS. Advances in Cognitive Neurodynamics III, Springer, June 2013, Proc. of 3rd International Conference on Cognitive Neurodynamics, Hokkaido, Japan, June 2011.

Firouzi M, Rostami MGh, Shouraki SB and Iloukhani M. (2010) A Novel Preisach Based Neural Network Approach to Hysteresis Non-Linearity Modeling. 2010 World Congress in Computer Science, Computer Engineering and Applied Computing - ICAI'10, 12-15 July 2010, Las Vegas, Nevada, USA pp 299-305.

Firouzi M, Shouraki SB and Conradt J. (2014) Sensorimotor Control Learning using a New Adaptive Spiking Neuro-Fuzzy Machine, Spike-IDS and STDP. 24th International Conference on Artificial Neural Networks pp 379-386.

Firouzi M, Glasauer S and Conradt J. (2014) Flexible Cue Integration by Line Attraction Dynamics and Divisive Normalization. International Conference on Artificial Neural Networks (ICANN), Hamburg, Germany pp 691-698.



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