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  • Neural nets : classical results and current problems

    Creator:
    Oregon State University. Dept. of Computer Science and Cull, Paul, 1943-
    Abstract:
    This note briefly discusses some of the classical results of McCulloch and Pitts. It then deals with some current research in neural nets. Several questions about neural nets are shown to be computationally difficult by showing that they are NP-Complete or worse. The size of neural nets necessary to compute...
    Resource Type:
    Research Paper
    Full Text:
    Department of Computer Science Oregon State University Corvallis, Oregon USA 97331{3202 pc@cs.orst.edu

  • A recurrent neural network implementation using the graphics processing unit

    Creator:
    Moore, Christopher
    Abstract:
    We took the back-propagation algorithms of Werbos for recurrent and feed-forward neural networks and implemented them on machines with graphics processing units (GPU). The parallelism of these units gave our implementations a 10 to 100 fold increase in speed. For nets with less than 20 neurons the machine performed faster...
    Resource Type:
    Masters Thesis
    Full Text:
    degree of Master of Science in Computer Science presented on October 23, 2009. Title: A Recurrent

  • A time-multiplexed switched-capacitor circuit for neural network applications

    Creator:
    Hansen, James Edward, 1962-
    Abstract:
    Analog computation in the form of neural networks is currently receiving much attention. Existing algorithms cannot be easily implemented in hardware because of the large number of neurons needed and the number of connections necessary between them. These problems have motivated development of alternatives to a conventional implementation. Hence, a...
    Resource Type:
    Masters Thesis
    Full Text:
    network applications AN ABSTRACT OF THE THESIS OF James Hansen for the degree of Master of Science in

  • An implementation and initial test of generalized radial basis functions

    Creator:
    Wettschereck, Dietrich
    Abstract:
    Generalized Radial Basis Functions were used to construct networks that learn input-output mappings from given data. They are developed out of a theoretical framework for approximation based on regularization techniques and represent a class of three-layer networks similar to backpropagation networks with one hidden layer. A network using Gaussian base...
    Resource Type:
    Masters Thesis
    Full Text:
    Science in Computer Science presented on June 27.1990. Title: An Implementation and Initial Test of

  • Analysis and synthesis of neural networks

    Creator:
    Skelton, Jeanette K.
    Abstract:
    The brain has long attracted the interest of researchers. Some tasks, such as pattern recognition and optimization, have proven to be exceptionally difficult for conventional computing systems to perform, but are executed by the brain almost effortlessly. Due to the large number of neurons and interconnections, it has proven impossible...
    Resource Type:
    Masters Thesis
    Full Text:
    THE THESIS OF Jeanette K. Skelton for the degree of Master of Science in Electrical and Computer

  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
    Resource Type:
    Dissertation
    Full Text:
    the degree of Doctor of Philosophy in Computer Science presented on December 8, 2016. Title: Parsing

  • Don't Fool Me : Detecting Adversarial Examples in Deep Networks

    Creator:
    Li, Xin
    Abstract:
    Deep learning has greatly improved visual recognition in recent years. However, recent research has shown that there exist many adversarial examples that can negatively impact the performance of such an architecture. Different from previous perspectives that focus on improving the classifiers to detect the adversarial examples, this work focuses on...
    Resource Type:
    Masters Thesis
    Full Text:
    of Science in Electric and Computer Engineering presented on September 26, 2016. Title: Don’t Fool

  • Object Tracking-by-Segmentation in Videos

    Creator:
    Chen, Sheng
    Abstract:
    This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of one or more targets in the image sequence. This is a very challenging task as algorithms need to deal with problems such as appearance variations,...
    Resource Type:
    Dissertation
    Full Text:
    degree of Doctor of Philosophy in Computer Science presented on March 7, 2017. Title: Object Tracking

  • Using Automation to Understand Sustainable Design Trade-Offs and to Promote Environmental Sustainability in the Early Design Phase

    Creator:
    Wisthoff, Addison K.
    Abstract:
    Sustainable product design is becoming an important component of the development of consumer products. Currently there are limited design resources to aid in the creation of environmentally sustainable products. The purpose of this research is to theorize a new method for integrating sustainable design knowledge into the early design phase...
    Resource Type:
    Masters Thesis
    Full Text:
    conducted by training an artificial neural network on 37 different consumer products. The results of this

  • Wave-by-wave Forecasting of Sea Surface Elevation for WEC Applications Utilizing NARX Neural Networks

    Creator:
    Gillespie, Alice
    Abstract:
    Forecasting of ocean waves over a short duration on the order of tens of seconds was approached with the optimization of wave energy conversion in mind. This study outlines the development of an artificial neural network model, specifically the Nonlinear Autoregressive Network with Exogenous Input (NARX), to predict a wave-by-wave...
    Resource Type:
    Masters Thesis
    Full Text:
    outlines the development of an artificial neural network model, specifically the Nonlinear Autoregressive