neural network

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neural network

A form of artificial intelligence that relies on a group of interconnected mathematical equations that accept input data and calculate an output. The more often the equations are used, the more reliable and valuable they become in drawing conclusions from data. Neural networks have been used in health care to interpret electrocardiograms and to make and suggest diagnoses.
Medical Dictionary, © 2009 Farlex and Partners

neural network

a proposed system of interconnecting neurones to explain the higher brain functions such as memory perception and learning, where the pattern of resulting activity can be varied through the number and strength of connections between the constituent neurones.
Collins Dictionary of Biology, 3rd ed. © W. G. Hale, V. A. Saunders, J. P. Margham 2005
References in periodicals archive ?
Watch a deep mind totally ace 'Space Invaders' After just four hours of game play, a deep neural net developed by Google's DeepMind has managed to come up with a Space Invaders strategy so optimal that it was better than any person's strategy.
Consciousness is an illusion of mind that is handily modeled by the Creativity Machine concept, wherein one internally perturbed neural net spontaneously generates the parade of memories, ideas, and feelings (all neuronal firing patterns) that we call "stream of consciousness." That is, those sensations and thoughts that appear to miraculously emerge from nowhere.
Each living robot is controlled with the help its own neural net that has a structure of two-layer artificial net.
Neural Net The results reported here derive exclusively from analyses based on standard neural nets using backpropagation based on standard logistic squashing, momentum, and varying learning rates (cf.
Nontechnical approaches useful to novice practitioners are found in both Denton (1995), who compares regression and neural nets, and McMenamin (1997), who presents a straightforward exposition on the statistical limits and advantages of neural networks.
Neural nets map information from one or more input nodes into an output node (equivalent to a regressand).
Dianhui Wang and Xiaohang Ma developed a hybrid scheme for intelligent image retrieval using neural nets. Each item in an image database is indexed by a visual feature vector, which is extracted using color moments and discrete cosine transform coefficients.
Hoptroff, R.G., 1993, "The Principles and Practice of Time Series Forecasting and Business Modeling Using Neural Nets," Neural Computing and Applications, 1, 59-66.
Among the analyzed neural nets, the radial basis function network generates the smallest classification errors.
Neural nets are a computational framework consisting of massively connected simple processing units.
The most common techniques for developing QSARs are regression analysis, neural nets, and classification methods.

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