Neuromorphic Computing: A Revolutionary Approach to Computing

Running head: NEUROMORPHIC COMPUTING
Neuromorphic Computing
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NEUROMORPHIC COMPUTING
Table of Contents
Introduction................................................................................................................................2
Discussion..................................................................................................................................3
History and Concept:..............................................................................................................3
Von Neumann versus Neuromorphic.....................................................................................4
Neuromorphic Chip:...............................................................................................................5
Neuromorphic and Artificial Intelligence..................................................................................5
Neuromorphic computing in Space:...........................................................................................6
Future Perspectives....................................................................................................................7
Application and benefits of Neuromorphic computing..............................................................8
Conclusion................................................................................................................................10
References................................................................................................................................11

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NEUROMORPHIC COMPUTING
Introduction
Neuromorphic computing is also referred as Neuromorphic engineering.
Neuromorphic computing has been a different approach than normal conventional
computing. The model of Neuromorphic was essential in the industry in order to consume
less energy and something that is has an enhanced version of computing. The industry
demanded a kind of technology that is more versatile and adaptable. Hence led the
development of Neuromorphic models (Adam et al., 2017). The aim of Neuromorphic
engineering was to encourage high and vibrant results that other traditional architectures
failed to. With the help of Neuromorphic computing the introduction of Neuromorphic chips
is possible. It is considered to be a great replacement for microprocessors. The Neuromorphic
chips are complex because the architecture is derived from the neurons of human brain. The
idea behind the creation of this chip was to easily achieve the trending technical goals. This
paper outlines the concept of Neuromorphic engineering and the development of
Neuromorphic models (Boybat et al., 2018). It also explains the application and benefits in
context of modern era and technologies. Neuromorphic computing is the enhanced version of
computing that can replace the numerical methods of computing. Hence to develop a unique
system it requires new architectures. The researchers started exploring the design of
Neuromorphic computing in 1990. They found that the analog computers which has been
working with the idea of nervous system of human was more powerful and efficient. The
traditional system lacked certain benefits like speech and image recognition (Brunner et al.,
2017). Therefore, the concept of using biological unit in computing technology has led to
additional improvement in the world of technologies.

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NEUROMORPHIC COMPUTING
Discussion
History and Concept:
The idea of Neuromorphic computing was initiated by Carver Mead in 1990. He
wanted to introduce a system that is faster in computation but requires less power (Grübl &
Baumbach, 2017). It specifies of an input neuron which generates pulse electric signals and
output Synapse that passes state to other neuron. Memristor generates neuroplasticity for
Neuromorphic computing. Neuromorphic computing was developed to compete with the
tradition architecture. The architecture of Neuromorphic computing was based upon human
brain. It was modeled with neurons and synapses (Burr et al., 2017). Neuromorphic
computing is one of the most outstanding invention oin the digital era. The concept can be
used to develop intelligent computers with high quality performance and mantainence. The
tool was a combination of machine learning and artificial intelligence with certain idea from
neuroscience. It includes components such as hardware, software, neuroscience and
computational science. It indicates the neural structure of human brain. The concept was
together inspired by biology, physics, mathematics and computer science. They are modeled
on the neurons which signals through nodes that delivers pulses in which the information is
carried by the frequency similar to the functioning of a nervous system in a human body. The
cell neural networking is implemented in Neuromorphic computing. It enables synapses to
get information and to identify patterns. It recognizes the texts without performing any
programming. It focuses on matching the traits of human brain. Carver Mead wanted to
create a computing model that works exactly like a human brain. Therefore he created
Neuromorphic computing which was flexible and could understand the unstructured stimuli.
The use of Spiking neural networks (SNNs) helps in generating original neural network of the
human brain. This concept has been inspired by the human brain (Esser et al., 2015). The
Neuromorphic computing is different from an artificial neuron network which is programmed