Biologically Sound Neural Networks for Embedded Systems Using OpenCL
نویسندگان
چکیده
Artificial neural networks (ANNs) are general function approximators and noise resistant, and therefore popular in many applications. Researchers in the field of computational intelligence have shown that biologically sound spiking neural networks (SNNs) are comparable, or even more powerful than traditional artificial neural networks(ANNs) [1]. However, such neural networks are usually computationally complex and often require high performance computers (or even supercomputers) to run them. In this paper we present the implementation of a very large SNN with spike response model (SRM) describing its neural dynamics using the OpenCL framework. This opens up new possibilities of real-time neural computing on embedded platforms.
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