Spiking Neural Networks I: Introduction #neuralnetworks #snn

Spike Neural Networks (SNNs) are a cutting-edge form of artificial neural networks that mimic the brain's communication through discrete spikes, offering a more energy-efficient and biologically plausible model compared to traditional ANNs. Leveraging spiking neuron models like Leaky Integrate-and-Fire (LIF) and Spike-Timing-Dependent Plasticity (STDP) for learning, SNNs excel in real-time processing, neuromorphic computing, and low-power applications. With growing applications in robotics, brain-machine interfaces, and cognitive computing, SNNs are poised to revolutionize AI by integrating spiking neural dynamics and neuromorphic hardware.

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