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Khadeer Ahmed
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2010 – 2019
- 2018
- [j2]Amar Shrestha
, Khadeer Ahmed, Yanzhi Wang, David P. Widemann, Adam T. Moody, Brian C. Van Essen
, Qinru Qiu:
Modular Spiking Neural Circuits for Mapping Long Short-Term Memory on a Neurosynaptic Processor. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 782-795 (2018) - 2017
- [c9]Amar Shrestha, Khadeer Ahmed, Yanzhi Wang, David P. Widemann, Adam T. Moody, Brian C. Van Essen, Qinru Qiu:
A spike-based long short-term memory on a neurosynaptic processor. ICCAD 2017: 631-637 - [c8]Amar Shrestha, Khadeer Ahmed, Yanzhi Wang, Qinru Qiu:
Stable spike-timing dependent plasticity rule for multilayer unsupervised and supervised learning. IJCNN 2017: 1999-2006 - 2016
- [j1]Qinru Qiu, Zhe Li
, Khadeer Ahmed, Wei Liu, Syed Faisal Habib, Hai (Helen) Li, Miao Hu:
A Neuromorphic Architecture for Context Aware Text Image Recognition. J. Signal Process. Syst. 84(3): 355-369 (2016) - [c7]Khadeer Ahmed, Qinru Qiu, Mangesh Tamhankar:
Distributed and configurable architecture for neuromorphic applications on heterogeneous cluster. HPEC 2016: 1-7 - [c6]Khadeer Ahmed, Amar Shrestha, Qinru Qiu:
Simulation of bayesian learning and inference on distributed stochastic spiking neural networks. IJCNN 2016: 1044-1051 - [c5]Khadeer Ahmed, Amar Shrestha, Qinru Qiu, Qing Wu:
Probabilistic inference using stochastic spiking neural networks on a neurosynaptic processor. IJCNN 2016: 4286-4293 - [c4]Khadeer Ahmed, Amar Shrestha, Yanzhi Wang, Qinru Qiu:
System Design for In-Hardware STDP Learning and Spiking Based Probablistic Inference. ISVLSI 2016: 272-277 - 2014
- [c3]Khadeer Ahmed, Qinru Qiu, Parth Malani, Mangesh Tamhankar:
Accelerating pattern matching in neuromorphic text recognition system using Intel Xeon Phi coprocessor. IJCNN 2014: 4272-4279 - [c2]Qinru Qiu, Zhe Li, Khadeer Ahmed, Hai (Helen) Li
, Miao Hu:
Neuromorphic acceleration for context aware text image recognition. SiPS 2014: 268-273 - 2011
- [c1]Anvith Katte Mahabalagiri, Khadeer Ahmed, Fred Schlereth:
A novel approach for simulation, measurement and representation of surface EMG (sEMG) signals. ACSCC 2011: 476-480
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