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	Neural network - Wikipedia, the free encyclopedia
		Neural network is sometimes used to refer to a branch of computational science that uses neural networks as models to either simulate or analyze complex phenomena and/or study the principles of operation of neural networks analytically.
		Neural networks, as used in artificial intelligence, have traditionally been viewed as simplified models of neural processing in the brain, even though the relation between this model and brain biological architecture is very much debated.
		Neural network software is used to simulate, research, develop and apply artificial neural networks, biological neural networks and in some cases a wider array of adaptive systems.
	en.wikipedia.org /wiki/Neural_networks (2947 words)

	Neural Networks Introduction
		Neural networks have been applied to a wide variety of different areas including speech synthesis, pattern recognition, diagnostic problems, medical illnesses, robotic control and computer vision.
		Neural networks have been shown to be particularly useful in solving problems where traditional artificial intelligence techniques involving symbolic methods have failed or proved inefficient.
		Such a neural network might be used to predict the ADR rate for new drugs, as well as to determine the properties that tend to make for "safe" drugs.
	uhavax.hartford.edu /compsci/neural-networks-tutorial.html (3432 words)

	Neural Nets
		Neural nets have the "topology of a directed graph" [Tayl93], meaning that, like the structure of the brain, connections between nodes or neurons is one-way.
		Neural networks are a natural extension of exploring the limits of computing, in terms of methodology and theory.
		Neural nets allow the programming of systems to solve "problems in which the rules governing the situation are unknown or difficult to use" [Tayl93] and to apply computing to problems not solvable in a strictly linear fashion.
	ei.cs.vt.edu /~history/NEURLNET.HTML (1422 words)

	Neural Networks & Connectionist Systems
		Neural models of intelligence emphasize the brain's ability to adapt to the world in which it is situated by modifying the relationships between individual neurons.
		Neural networks are usually characterized in terms of the number and types of connections between individual processing elements, called neurons, and the learning rules used when data is presented to the network.
		Neural networks, unlike fuzzy logic, seek to reproduce the versatility of the human brain in recognizing the end-to-end, input-to-output behavior of a system without understanding all the processes taking place within it.
	www.aaai.org /aitopics/html/neural.html (4330 words)

	Thinking About Thought: Consciousness, Life and Meaning
		Neural networks must exhibit the same property is they have to be useful for practical purposes and plausible as models of the brain.
		Neural networks belong to a more general class of processing systems, parallel distributed processors, and neurocomputing is a special case of Parallel Distributed Processing, or PDP, whereby processing is done in parallel by a number of independent processors and control is distributed over all processes.
		Formally: a neural net is a nonlinear directed graph in which each element of processing (each node) receives signals from other nodes and emits a signal towards other nodes, and each connection between nodes has a weight that can vary in time.
	www.thymos.com /tat/neural.html (3076 words)

	Neural Integrator Introduction
		Neural nets are useful for working on many types of relatively complex problems that do not easily yield to straightforward or algorithmic analysis.
		Structurally, the various neural networks resemble what people suppose to be the operation of a living brain or at least its major information processing components, primarily neurons and synapses.
		Since training neural nets is a major part of their design, the topic will be discussed in more detail later.
	www.neuralintegrator.com /intro (1387 words)

	Neural Prosthesis Program (NPP): National Institute of Neurological Disorders and Stroke (NINDS)
		Neural prosthetic devices are artificial extensions to the body that restore or supplement function of the nervous system lost during disease or injury.
		Neural prosthetics are devices that are used to allow disabled individuals the ability to control their own bodies and lead fuller and more productive lives.
		Of particular interest to the NINDS is future progress in the field of neural prosthetics that will result in assistive technologies to improve the quality of life by restoring motor and communicative functions for individuals with spinal cord injuries, Amyotrophic Lateral Sclerosis, and stroke.
	www.ninds.nih.gov /funding/research/npp (976 words)

	Connectionism (Stanford Encyclopedia of Philosophy)
		Neural networks are simplified models of the brain composed of large numbers of units (the analogs of neurons) together with weights that measure the strength of connections between the units.
		If a neural net were to model the whole human nervous system, the input units would be analogous to the sensory neurons, the output units to the motor neurons, and the hidden units to all other neurons.
		Neural networks are also particularly well adapted for problems that require the resolution of many conflicting constraints in parallel.
	plato.stanford.edu /entries/connectionism (6660 words)

	Neural 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.
		The commonest type of artificial neural network consists of three groups, or layers, of units: a layer of "input" units is connected to a layer of "hidden" units, which is connected to a layer of "output" units.
		Neural networks were used to discover the influence of undefined interactions by the various variables.
	www.doc.ic.ac.uk /~nd/surprise_96/journal/vol4/cs11/report.html (6614 words)

	Artificial neural network - Wikipedia, the free encyclopedia
		A neural network is an interconnected group of nodes, akin to the vast network of neurons in the human brain.
		These networks are also similar to the biological neural networks in the sense that functions are performed collectively and in parallel by the units, rather than there being a clear delineation of subtasks to which various units are assigned (see also connectionism).
		Training a neural network model essentially means selecting one model from the set of allowed models (or, in a Bayesian framework, determining a distribution over the set of allowed models) that minimises the cost criterion.
	en.wikipedia.org /wiki/Artificial_neural_network (5626 words)

	Game Potato, The one stop gaming shop! - Neural Cluster (Site not responding. Last check: 2007-11-02)
		Neural Cluster is designed to keep track of the exhausting number of tasks a project may have in real time.
		Neural Cluster is designed on this principle, but in a way so that it can be used quickly and efficiently.
		Neural Cluster allows you to write down any issues, ideas, concerns, or tasks while working on your computer with minimal interruption.
	www.gamepotato.com /ncindex.html (479 words)

	PC AI - Neural Nets
		The neural network is configured for a specific application, such as data classification or pattern recognition, through a learning process called training.
		Neural networks can differ on: the way their neurons are connected; the specific kinds of computations their neurons do; the way they transmit patterns of activity throughout the network; and the way they learn including their learning rate.
		In general, neural networks are well suited to problems that people are good at solving, but for which computers generally are not.
	www.pcai.com /web/ai_info/neural_nets.html (1747 words)

	Neural Networks (Site not responding. Last check: 2007-11-02)
		The purpose of the Council is to advance and coordinate work in the field of Neural Networks carried out throughout the IEEE and as such is exclusively scientific, literary and educational in character.
		The European Neural Network Society (ENNS) is an association of scientists, engineers, students, and others seeking to learn about and advance our understanding of the modelling of behavioral and brain processes and to apply neural modelling concepts to problems relevant in many different domains.
		This neural network simulator provides an attrative graphical user interface through which neural networks may be created, trained and used to classify data.
	www.insead.edu /CALT/Encyclopedia/ComputerSciences/AI/neuronet.htm (532 words)

	Neural Group of Companies (Site not responding. Last check: 2007-11-02)
		Over the years, NEURAL has grown substantially and it has developed the capabilities and capacity to deliver quality services and innovative system solutions to meet the challenges of the market needs in line with the accelerated technological changes where we can expand the technology to differing market segments and needs.
		Today, NEURAL is proud of its achievements, with numerous successful undertakings for various renowned clients.
		NEURAL Group of Companies have since been unrelentlessly pursuing performance and result demanded by all, from big conglomerates to SMI’s and government bodies.
	www.neural.com.my (142 words)

	[No title]
		Neural Networks are analytic techniques modeled after the (hypothesized) processes of learning in the cognitive system and the neurological functions of the brain and capable of predicting new observations (on specific variables) from other observations (on the same or other variables) after executing a process of so-called learning from existing data.
		A practice (used in neural networks) designed to prevent overlearning during back propagation training, by adding random noise to input patterns during training (and so "blurring" the position of the training data).
		In neural networks, nominal output variables are used to distinguish classification tasks from regression tasks.
	www.statsoft.com /textbook/glosn.html (2016 words)

	NeuroDimension - Neural Network Software, Neural Net Software, Neural Networks, Neural Nets
		Neural networks and genetic algorithms are exciting technologies in the field of artificial intelligence.
		Our neural network software products are among the most powerful and flexible on the market today, yet their intuitive graphical user interfaces make them incredibly easy to use.
		This advanced technical analysis trading software combines neural network and genetic algorithm technologies with traditional technical analysis to create a highly effective tool for financial modeling.
	www.nd.com (496 words)

	Cogprints - Subject: Neural Nets (Site not responding. Last check: 2007-11-02)
		Cangelosi, Angelo and Parisi, Domenico and Nolfi, Stefano (1994) Cell division and migration in a 'genotype' for neural networks.
		Marshall, J.A. and Schmitt, C.P. and Kalarickal, G.J. and Alley, R.K. Neural model of transfer-of-binding in visual relative motion perception.
		Cangelosi, A and Parisi, D (1998) The emergence of a "language" in an evolving population of neural networks.
	cogprints.org /view/subjects/comp-sci-neural-nets.html (5296 words)

	NJIT - PublicInfo: Neural Engineering
		Neural Engineering is an emerging discipline that uses engineering techniques to investigate the function and manipulate the behavior of living neural tissue, with the goal of enhancing human performance and information processing capabilities.
		Neural engineering is recognized to be one of the premiere growth areas of the 21st century.
		NJIT is focusing on research into neural plasticity, the flexible nature of neurons that allows them to be “retrained” for different functions.
	www.njit.edu /publicinfo/publibrary/report2004/neural.php (313 words)

	developer : Neural Surround
		Neural Surround is scalable n-channel rendering technology that enables play back in surround sound from stereo, matrix encoded stereo (Lt, Rt) or watermarked discrete surround content.
		Neural Surround is available as an Audio Stream Processing (ASP) algorithm plug in compatible with most DSP platforms used in surround sound receiver systems.
		Neural Audio also has available Neural Surround Development System as separate processor units that can be deployed with any radio or receiver system that has a stereo RCA output capability.
	www.neuralaudio.com /SEE.html (226 words)

	Neural Networks Software: Train, Visualize, and Validate Neural Network Models
		Artificial neural networks have revolutionized the way researchers solve many complex and real-world problems in engineering, science, economics, and finance.
		Neural Networks also includes special functions to address typical problems in data analysis, such as function approximation, classification and detection, clustering, nonlinear time series, and nonlinear system identification problems.
		Neural Networks 1.0.2 requires Mathematica 5.0.1 or higher and is available for all Mathematica platforms.
	www.wolfram.com /products/applications/neuralnetworks (339 words)

	Neural Prosthesis.com - Biomimetic Implants for the Brain - Biomedical Engineering
		Home of research on the development of biomimetic models of hippocampus to serve as neural prostheses for lost cognitive and memory function.
		The continuing development of implantable neural prostheses signals a new era in bioengineering and neuroscience research.
		The BMSR in the Department of Biomedical Engineering at USC is dedicated to the advancement of the state-of-the-art in biomedical modeling and simulation through core and collaborative research projects.
	www.neural-prosthesis.com (351 words)

	Neural Nets
		NXL is a C language implementation of a neural net which learning algorithm and structure are closely inspired from Scott Fahlman's QuickProp.
		While it can be used as is for small neural modeling applications, it is recommended to acquire the VBA code, to better customize it to your application environment.
		Many neural nets do not generalize well on account of "neuronal glut", and it is always advisable to build smaller nets.
	www.foretrade.com /neural_nets.htm (350 words)

	Neural Tutorials
		However, neural networks have not yet been established as a valid and reliable method in the business forecasting domain, either on a strategic, tactical or operational level.
		In addition, the attendees are invited to download a CD containing 22+ demo-programs of leading Neural Networks software companies, along with the example datasets to start experimenting and working with Neural Networks straight away.
		Neural network architectures such as the feedforward backpropagation, Hopfield, and Kohonen networks are discussed.
	www.neural-forecasting.com /tutorials.htm (871 words)

	An Introduction to Neural Networks
		Neural networks cannot do anything that cannot be done using traditional computing techniques, BUT they can do some things which would otherwise be very difficult.
		This is one of the first large-scale applications of neural networks in the USA, and is also one of the first to use a neural network chip.
		IEEE Computational Intelligence Society (was IEEE Neural Networks Society) http://www.ieee-cis.org/ publish a number of journals on neural networks and related areas.
	www.cs.stir.ac.uk /~lss/NNIntro/InvSlides.html (2217 words)

	What is neural network? - A Word Definition From the Webopedia Computer Dictionary (Site not responding. Last check: 2007-11-02)
		Neural networks are particularly effective for predicting events when the networks have a large database of prior examples to draw on.
		Neural networks are currently used prominently in voice recognition systems, image recognition systems, industrial robotics, medical imaging, data mining and aerospace applications.
		The Foundation for Neural Networks is a non-profit reasearch organization which promotes the exploration and development of neural networks.
	www.webopedia.com /TERM/n/neural_network.html (407 words)

	Neural Publications
		However, very few books are dedicated to this topic, focussing either on the technical specification of neural networks as a method, or the forecasting domain.
		They incorporate general introductions to Neural Networks or Forecasting as well as specific Literature on Forecasting with NN, although there are very few dedicated publications to date.
		Abstract: Interest in using artificial neural networks (ANNs) for forecasting has led to a tremendous surge in research activities in the past decade.
	www.neural-forecasting.com /neural_forecasting_publications.htm (488 words)

	Neural Networks (Site not responding. Last check: 2007-11-02)
		However, it does a fair job in small neural applications, where one shall try and predict a value based on small patterns (ideally 5, or up to 10 inputs), over around 1000 examples in the training set.
		Although this neural net utility could be used for many purposes, we have kept a historical split, i.e.
		In a nutshell, the neural net can stop training on time limit, number of iterations (data scans), max error swing, error stagnation, calculated either on the training or test sets.
	www.foretrade.com /neural_net.htm (1576 words)

	Neural (Site not responding. Last check: 2007-11-02)
		I don't do skull or spinal radiographs for most neural cases, but they would be appropriate if the exam revealed pain or abnormalities on spinal palpation or neck manipulation. Or if we suspect a possible mass or other problem in the head.
		While an experienced veterinarian can often guess what disease is likely, or even successfully treat your pet without knowing exactly which neural disease it has, don't expect a definitive diagnosis without a fair amount of expensive testing.
		Also, many times the neural signs are the result of disease in other organs. ; Diabetes, liver disease, endocarditis, and bacterial invasion through unhealthy gut or gums are examples.
	animalpetdoctor.homestead.com /Neural.html (5565 words)

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