A neuromorphic VLSI circuit for spike-based random sampling

This paper presents a novel, neuromorphic circuit that produces a continuous stream of analog random samples. The circuit encodes these samples by the temporal difference between the onset times of two subsequent voltage jumps, which mimic action potentials of biological neurons. By combining elegantly concepts from renewal theory and analog very large scale integrated technology, the circuit is principally able to sample from arbitrary distributions of positive, real random variables. Moreover, these distributions can be defined online by the circuit-user in terms of an input current time-series, without the need to reconfigure the circuit. We show results from this circuit fabricated in a CMOS 0.35- $\mu \text{m}$ technology process. Random sampling is demonstrated for the uniform, exponential, and—by means of circuit simulation—also for a more complex bimodal distribution.