The artificial neural network is nothing but the information-processing paradigm, which is inspired by a way of biological nervous systems including brain and process information. A key element of the paradigm is a novel structure of an information processing system. This is composed big number of the highly interconnected elements that is neurons that working in the unison to solve the specific problems. The artificial neural network is configured for the specific application including data classification or pattern recognition via the learning process. By learning in the biological system absorbs the adjustments into a synaptic connections, which exist in between neurons. It is fact of the artificial neural network as well.
Uses Of Neural Network:
The neural networks with the remarkable ability to derive the meaning from the imprecise or complicated data and it used to extract the patterns and also used to detect the trends, which are very difficult, be noticed by the humans or the other computer tech. The trained artificial neural network thought of expert in a category of the information that has to analyze. These expert used to give the projections given fresh situations of the interest and the answer for what if questions.
Advantage Of Neural Network:
- The adaptive learning is the ability to learn about how to do the tasks depends on a data is given for the training or the initial experience.
- The self-organization, the artificial neural network will create the own organization or the representation of an information this receives while the learning time.
- The real time operation, the artificial neural network computations can be carried out of the parallel and the special hardware devices being designed and also manufactured that take an advantage of the capability.
- The fault tolerance through the redundant information coding, the partial destruction of the network leads into a corresponding degradation of the performance. The network capabilities can be retained with the main network damage.
Neural Network Vs Conventional Computers:
The Neural Networks Technology takes various approach to problem solving the conventional computers. The conventional computers use the algorithmic approach that is a computer follows the set of the instruction in terms of to solve the problem. Unless specific steps the computer requires to follow known a computer cannot solve a problem. Restrict a problem solving ability of the conventional computers into the problems.
The neural network process information in the same way a human brain does. A network has composed the big number of interconnecting processing elements that is neurons working in a parallel to solve the specific problem.
How It Work:
A basic processing element of the neural network is the neuron. These building block of the human awareness have encompassed the few general capabilities. The biological neuron had received the inputs from the other sources and combines in some of the way, also performs the nonlinear operation on a result and outputs a final result. Within the humans, so many variations are available on a basic type of the neuron.