Neuromorphic hardware design is gaining popularity day by day. Neuromorphic hardware is a branch of machine learning and artificial intelligence. Neuromorphic hardware are important because the Moore’s law which has led the silicon industry is moving towards saturation.

 

Dr. Saad Qasim Khan is an assistant professor in NED University of Engineering and Technology who has done his Ph.D. in the field of Neuromorphic Hardware Design is an expert in the area. His research thesis includes designing a frequency  dependent synaptic plasticity which is different than the conventional neural network models used today.

Conventional models rely on a weight value with synaptic connections based on the Hebbian theory of learning. Frequency based plasticity model is based on the concept that the synaptic connection serves as a bandpass filtering element selectively passing presynaptic information. The said work can be viewed at;

[https://www.inderscienceonline.com/doi/abs/10.1504/IJBIC.2020.109001]

For further queries and information related to the frequency based plastcity model please contact Dr. Saad Qasim Khan at saadqasimkhan(@)neduet(dot)edu(dot)pk)

Dr. Saad Qasim Khan

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