An Event-Based Digital Time Difference Encoder Model Implementation for Neuromorphic Systems

IEEE Transactions on Neural Networks and Learning Systems(2022)

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摘要
Neuromorphic systems are a viable alternative to conventional systems for real-time tasks with constrained resources. Their low power consumption, compact hardware realization, and low-latency response characteristics are the key ingredients of such systems. Furthermore, the event-based signal processing approach can be exploited for reducing the computational load and avoiding data loss due to it...
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关键词
Computational modeling,Encoding,Neurons,Task analysis,Synapses,Real-time systems,Neuromorphics
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