Definitions for neuromorphic engineering
neu·ro·mor·phic en·gi·neer·ing

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1. Neuromorphic engineering

   Neuromorphic computing is an approach to computing that is inspired by the structure and function of the human brain. A neuromorphic computer/chip is any device that uses physical artificial neurons (made from silicon) to do computations. In recent times, the term neuromorphic has been used to describe analog, digital, mixed-mode analog/digital VLSI, and software systems that implement models of neural systems (for perception, motor control, or multisensory integration). The implementation of neuromorphic computing on the hardware level can be realized by oxide-based memristors, spintronic memories, threshold switches, transistors, among others. Training software-based neuromorphic systems of spiking neural networks can be achieved using error backpropagation, e.g., using Python based frameworks such as snnTorch, or using canonical learning rules from the biological learning literature, e.g., using BindsNet.A key aspect of neuromorphic engineering is understanding how the morphology of individual neurons, circuits, applications, and overall architectures creates desirable computations, affects how information is represented, influences robustness to damage, incorporates learning and development, adapts to local change (plasticity), and facilitates evolutionary change. Neuromorphic engineering is an interdisciplinary subject that takes inspiration from biology, physics, mathematics, computer science, and electronic engineering to design artificial neural systems, such as vision systems, head-eye systems, auditory processors, and autonomous robots, whose physical architecture and design principles are based on those of biological nervous systems. One of the first applications for neuromorphic engineering was proposed by Carver Mead in the late 1980s.

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1. Neuromorphic engineering

   Neuromorphic engineering, also known as neuromorphic computing, is a concept developed by Carver Mead, in the late 1980s, describing the use of very-large-scale integration systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system. In recent times the term neuromorphic has been used to describe analog, digital, and mixed-mode analog/digital VLSI and software systems that implement models of neural systems. A key aspect of neuromorphic engineering is understanding how the morphology of individual neurons, circuits and overall architectures creates desirable computations, affects how information is represented, influences robustness to damage, incorporates learning and development, adapts to local change, and facilitates evolutionary change. Neuromorphic engineering is a new interdisciplinary discipline that takes inspiration from biology, physics, mathematics, computer science and engineering to design artificial neural systems, such as vision systems, head-eye systems, auditory processors, and autonomous robots, whose physical architecture and design principles are based on those of biological nervous systems.

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How to say neuromorphic engineering in sign language?

Numerology

1. Chaldean Numerology

   The numerical value of neuromorphic engineering in Chaldean Numerology is: 5

2. Pythagorean Numerology

   The numerical value of neuromorphic engineering in Pythagorean Numerology is: 1

References

1. ^ Wikipedia
   https://en.wikipedia.org/wiki/Neuromorphic_Engineering
2. ^ Wikidata
   https://www.wikidata.org/w/index.php?search=neuromorphic engineering