SIMULATION OF SPARSE RANDOM NETWORKS ON A CNAPS SIMD NEUROCOMPUTER

Neurons of the cortical tissue in a mammalian brain are connected in an extremely sparse and random fashion We use ndings of neuroanatomy to model this special connection scheme and present methods for a parallel simulation of such networks on a digital CNAPS neurocomputer A considerable speedup in comparison to sequential computation is achieved Biologicallyinspired sensorimotor systems embedded in complex environments are models for investigating the principles of biological information processing A real time simulation of neural networks for such systems demands an ex tremely high computing performance Although hardware implementation