A parallel DSP-based neural network emulator with CMOS VLSI packet switching hardware

This work describes a parallel neural network emulator which uses standard DSPs and application-specific VLSI communication processors with an integrated hardware routing algorithm. The use of DSPs as programmable processing elements enables the emulation of different types of neurons including biologically inspired models with learnable synaptic weights and delays, variable neuron gain, and static and dynamic thresholding. Locally interconnected communication processors attached to each DSP can span up a 2D- or 3D-computing grid and thus form a highly parallel network topology capable of global packet switched routing