By definition, a neutral network is a set of CPUs which work in parallel in an attempt to simulate the way the human brain works, although in greatly simplified form.
A neutral network processor is a CPU that takes the modeled operation of how a human brain works on a single chip.
Neutral network processors reduce the requirements for brain-like computational processing of entire computer networks that excel in complex applications such as artificial intelligence, machine learning, or computer vision down to a multi-core chip.
In other words, astificial neutral networks are a computational model that consists of a set of units, called artificial neurons, connected to each other to transmit signals. The input information traverses the neutral network (where it undergoes various operations) producing output values. Its name and structure are inspired by the human brain, mimicking the way biological neurons signal each other.
So the goal of the neutral network is to solve problems in the same way as the human brain, although neural networks are more abstract.
In summary, a neutral network is a set of CPUs which work in parallel in an attempt to simulate the way the human brain works, although in greatly simplified form.
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A process will get more quanta per scheduling cycles. This is used to give more important process a larger share of the CPU.
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B. Information security analysis.
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