We use cookies to create the best experience for you. Keep on browsing if you are OK with that, or find out how to manage cookies.
Nobody downloaded yet

Neural Network - Essay Example

Comments (0)
Summary
Neural networks have seen an explosion of interest over the last few years, and are being successfully applied across an extraordinary range of problem domains, in areas as diverse as medicine, engineering, geology, finance and physics. Indeed, anywhere that there are problems of prediction, classification or control, neural networks are being introduced.
Download full paper
GRAB THE BEST PAPER
Neural Network
Read TextPreview

Extract of sample
Neural Network

Download file to see previous pages... In general a biological neural network is composed of a group or groups of chemically connected or functionally associated neurons. A single neuron may be connected to many other neurons and the total number of neurons and connections in a network may be extensive. These connections are called synapses, are usually formed from axons to dendrites, though dendrodendritic microcircuits and other connections are possible. Apart from the electrical signaling, there are other forms of signaling that arise from neurotransmitter diffusion, which have an effect on electrical signaling. As such, neural networks are extremely complex (Arbib 2002). Now a day the term neural network often refers to artificial neural networks, which are composed of artificial neurons or nodes.
Biological neural networks which are made up of real biological neurons. These Biological neural networks are connected or functionally related in the peripheral nervous system or the central nervous system. They are often identified as groups of neurons that perform a specific physiological function in laboratory analysis.
Artifi
Artificial neural networks are made up of interconnecting artificial neurons that mimic the properties of biological neurons. Artificial neural networks may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The real, biological nervous system is highly complex and includes some features that may seem superfluous based on an understanding of artificial networks.
Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques. A trained neural network can be thought of as an 'expert' in the category of information it has been given to analyze. After analyzing, this expert answers the 'what if' questions.

Other advantages of Neural Network include:
Adaptive learning: An ability to learn how to do tasks based on the data given for training or initial experience.
Self-Organization: An Artificial Neural Network can create its own organization or representation of the information it receives during learning time.
Real Time Operation: Artificial Neural Network computations may be carried out in parallel, and special hardware devices are being designed and manufactured which take advantage of this capability.
Fault Tolerance via Redundant Information Coding: Partial destruction of a leads to the corresponding degradation of performance. However, some network capabilities may be retained even with major network damage.
Biological Neural Networks
Most living creatures, which have the ability to adapt to a changing environment, need a controlling unit which is able to learn. Higher developed animals and humans use very complex networks of highly specialized neurons to perform this task.
The control unit or brain can be divided in different anatomic and functional sub-units, each having ...Download file to see next pagesRead More
Comments (0)
Click to create a comment
CHECK THESE SAMPLES - THEY ALSO FIT YOUR TOPIC
Neural Networks for handwriting recognition
stems in every walk of life, automatic handwriting recognition based systems have appeared as one of the major commercial and academic interests. At the present, there exist a large number of algorithms to identify handwritten digits. Additionally, new technology based systems implemented in post offices and other departments make use of them to sort people letters, in the same way banks and other financial institutions make use of them to read people checks for ensuring authentication.
16 Pages(4000 words)Essay
Network analysis
In doing this, it is vital that connections have to be created by which each member could relate to everyone in a particular way, leading to spatial interactions and design practices to be formulated (Burke and Tierney, 2007). From the past, a businessman for instance has strong reliance on successfully creating a network because of the associated benefits with it for his business.
6 Pages(1500 words)Essay
Intelligent systems - neural networks
Neural nets are used in bioinformatics to map data and make predictions. As EasyNN-Plus is tool/program/software used to create a neural network system for Microsoft Windows, it helps the creation of neural networks easy. It allows the user to produce multilayer neural networks from a grid or from text files and images.
13 Pages(3250 words)Essay
Connectionists Modelling in Letter and Words Recognition
There are many forms of connectionism, but the most common forms use neural network models. Connectionist networks have been used to model a wide range of cognitive phenomena, including developmental, neuropsychological and normal adult behaviours. A mental phenomena is described by interconnected network of simple units.
3 Pages(750 words)Essay
Neural System Development
Two major classes of cells generate within neural tube cells forming the majority of the nervous system; neurons and glia (Gill 2008). Both classes of cells differentiate into many different types generated with highly specialized functions and shapes. This section covers the establishment of neural populations, the inductive influences of surrounding tissues and the sequential generation of neurons establishing the layered structure seen in the brain and spinal cord.
3 Pages(750 words)Essay
Network Intrusion Detection Systems
It is the most important component of the network system. It is mandatory for the network systems to install an intrusion detection system to easily manage the attacks and resolve the issues. (Mun 2009). There are various types of intrusion systems and they are implemented based on the network system.
6 Pages(1500 words)Essay
Pattern Recognition Using Neural Network
Above two are common letters of English alphabet. Task of a pattern recognizer is to characterize these two images as 'a' and 'b', no matter how they are aligned with reference axis unless and until they are not getting conflicted with other characters. Last line means to say that if the letters are placed in some tilted position, then also algorithm must tackle this problem.
12 Pages(3000 words)Essay
Neural Network
Above two are common letters of English alphabet. Task of a pattern recognizer is to characterize these two images as ‘a’ and ‘b’, no matter how they are
11 Pages(2750 words)Essay
Learning and Hopfield Networks
The Hopfield networks are known to provide a proper understanding of human memory. There is a recall pattern that is found in the Hopfield network which closely relates to the recall mechanism in humans. If there is any destruction of the neurons of the network,
5 Pages(1250 words)Essay
Learning and Hopefield Networks
There exists a gap between two nerve cells where they meet and it is known as the synaptic cleft. The part of the neurons existing on either side of the synaptic cleft are called a
4 Pages(1000 words)Essay
Let us find you another Essay on topic Neural Network for FREE!
Contact us:
+16312120006
Contact Us Now
FREE Mobile Apps:
  • About StudentShare
  • Testimonials
  • FAQ
  • Blog
  • Free Essays
  • New Essays
  • Essays
  • The Newest Essay Topics
  • Index samples by all dates
Join us:
Contact Us