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Temporal Influence On Awareness, Don E. Hill
Temporal Influence On Awareness, Don E. Hill
Theses and Dissertations
Grossberg's Motion Oriented Contrast Filter (MOC) was extensively analyzed (7). The output from the filter's "global motion" neuronal layer was compared to a noncausal post-processing filter developed by AFIT. Both filters were shown to incorporate a weighted, noncausal temporal range of input data in processed output. The global motion framework was then implemented using a physiologically motivated pulsed neural model - the Pulse Coupled Neural Network (PCNN). By incorporating both spatial and temporal data, the PCNN was shown to exhibit a common visual illusion, apparent motion. The existence of a physiological temporal processing range was further investigated through implementation of …
Semantic Interpretation Of An Artificial Neural Network, Stanley D. Kinderknecht
Semantic Interpretation Of An Artificial Neural Network, Stanley D. Kinderknecht
Theses and Dissertations
Recent advances in machine learning theory have opened the door for applications to many difficult problem domains. One area that has achieved great success for stock market analysis/prediction is artificial neural networks. However, knowledge embedded in the neural network is not easily translated into symbolic form. Recent research, exploring the viability of merging artificial neural networks with traditional rule-based expert systems, has achieved limited success. In particular, extracting production (IF.. THEN) rules from a trained neural net based on connection weights provides a valid set of rules only when neuron outputs are close to 0 or 1 (e.g. the output …
The Mathematics Of Measuring Capabilities Of Artificial Neural Networks, Martha A. Carter
The Mathematics Of Measuring Capabilities Of Artificial Neural Networks, Martha A. Carter
Theses and Dissertations
Researchers rely on the mathematics of Vapnik and Chervonenkis to capture quantitatively the capabilities of specific artificial neural network (ANN) architectures. The quantifier is known as the V-C dimension, and is defined on functions or sets. Its value is the largest cardinality 1 of a set of vectors in Rd such that there is at least one set of vectors of cardinality 1 such that all dichotomies of that set into two sets can be implemented by the function or set. Stated another way, the V-C dimension of a set of functions is the largest cardinality of a set, such …
Nonlinear Time Series Analysis, James A. Stewart
Nonlinear Time Series Analysis, James A. Stewart
Theses and Dissertations
This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series. Two approaches to feature selection are used. First, a subset enumeration method is used to determine which financial indicators are most useful for aiding in prediction of the S&P 500 futures daily price. The candidate indicators evaluated include RSI, Stochastics and several moving averages. Results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages. The second approach to feature selection is calculation of individual saliency metrics. A new decision boundary-based individual saliency …