What is nervous programming?
neural programming is used to create a software that mimics the basic functions of the brain. It is a key part of artificial intelligence (AI) and creates software that can anticipate unknown, such as weather trends and stock markets, as well as games in which a cyber opponent improves, as he gains experience. The advantage of nervous programming over traditional programming is its software to learn and adapt to new data. Each artificial neuron is induced by a certain numeric value that determines when and where it sends a signal to another neuron. One neuron is programmed by a simple IF-thine rule for a basic task. If the data is -1, it will perform one function. If the data value is 0, it does something else.
neural programming is a two -stage process. The first year is to enter basic information and rules that the software application must understand the data it receives. This software is usually programmed with bits of bias, which gives greater credibility to a certain typeto the information. For example, neural software programming on the stock market will include the basic function of stock market trading, such as the assumption that greater demand for stock increases its value. It will also include some distortion, for example, as software should pay close attention to trends in quarterly income reports.
The second step in neural programming is called training. Data is used to teach software certain trends and possibilities; In general, the more data receives the software, the better it happens when creating accurate outputs. For example, data can teach a computer that when a certain industry has strong revenue from the second quarter, it is generally MEANS its fourth quarter is slow. Stock values are tied to earnings reports, so the software could eventually predict that shares for this sector will decline after the fourth quarter reports when industry will be strong second quarterting. Finally, the software output could advise the merchant to sell before the news of the fourth quarter earnings.
It is usually an advantage of neural programming that software for functioning does not need perfect information. Unlike traditional programming that closes when errors occur, nerve programming can adapt to imperfect inputs using past information to solve the problem. This is how the human brain also works, although it is much more complicated. For example, one could be able to recognize an old friend, even if the friend brought weight or grew up beard; Other aspects of a friend - facial structure, eyes, way of walking or voice - evoke recognition. Neural programmers will continue to specify that not only mimics the brain, but in some cases it will be faster and even more accurate.