Spike Encoding

Spike encoding, the process of representing information as sequences of neuronal spikes, is a central theme in neuromorphic computing and neuroscience, aiming to bridge the gap between biological and artificial neural systems. Current research focuses on developing efficient spike encoding algorithms and architectures, such as Spiketrum and various SNN (Spiking Neural Network) models, for diverse applications including audio processing, image recognition, and control systems. These efforts are driven by the potential for energy-efficient, robust, and biologically plausible computation, impacting fields ranging from brain-computer interfaces to low-power sensory processing.