… computing, most clearly in a visionary 1990 paper by the California Institute of Technology
(Caltech)’s Carver Mead that established the term “neuromorphic.” Yet industry’s steady …

… computing that requires significant memory updates (see Figure 1). By contrast, neuromorphic
computing … improvement in computational capability for specific types of analyses. Like the …

… Neuromorphic computing takes inspiration from the brain to create energy-efficient …
neuromorphic computing. We review striking results that leverage physics to enhance the computing …

… of neuromorphic hardware and algorithms. Our survey indicates that neuromorphic engineering
… with growing data volumes, and the imminent need for intelligent, versatile computing. …

… to define the computational complexity of a neuromorphic algorithm. We explic… time
complexities mean in the context of neuromorphic algorithms based on our model of neuromorphic …

… Here we provide an overview of the developments in neuromorphic computing for both …
We discuss the main challenges and the future prospects of neuromorphic computing, with …

… neuromorphic computing systems. In this paper, we review the evolution of neuromorphic
computing technique in both computing … the landscape of neuromorphic computing in the future…

… the search for an approach to push computing technology much further. Neuromorphic
Computing is a way through which we can approach the next generation of computer technology. …

… and classified using a neuromorphic computing approach by … We show that all ML, DL and
neuromorphic computing … , “Neuromorphic computing gets ready for the (really) big time,” …

… and RC [= spike-time dependent plasticity and reservoir computing, respectively] guidance
for the … — so we extended our perspective to neuromorphic computing in general. Second, we …