Thesis - Department of Electronic & Computer Engineering

tion. Thus the power consumption is minimized. The communication channel isaccessed and energy is expended by active neurons only. Because generally very fewneurons within a network are active at any one time, AER is more efficient at transmittingthis sparse representation of data across the neural population than the non-eventdriven multiplexing method such as scanning used in earlier neuromorphic work.Different from the biological communication channel, contention will occur if twoor more neurons attempt to spike simultaneously when random access to the sharedcommon bus are provided. Thus collisions must be expected and handled properly. Wecan simply detect and ignore the collided pulses, or use an arbitration scheme to serializesimultaneous events. We can hold all the waiting pulses in the queue until they areselected by the arbiter, or discard the aging pulses when they are no longer of interestand can be regarded as noise. According to the way how the collisions are handled, thereported AER communication schemes can be classified into the following two maingroups: Non-arbitered and Arbitered.3.1.1 Non-arbiteredIn the non-arbitered scheme, all output units have access to one common bus, onwhich the code identifying each neuron is wired. When activity in a neuron determinesa pulse emission, and if no other pulses are simultaneously emitted, the bus configurationcarries the identity of the emitting neuron for the duration of a pulse. Pulses aredecoded by the receiver, and directed to the units on the target chips. Whenever 2 ormore neurons attempt to access the channel at the same time, the coding ensures thatthe resulting bus configuration is not valid and automatically ignored by the decoder.To test the performance of the communication system exploiting non-arbiteredscheme, Mortara has reported a system in [12] as an variation of the original AER ofMahowald. The goal of the system is to map the activities of an array of cells in the19