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Conservative Thirty Calendar Day Stock Prediction Using A Probabilistic Neural Network, H. Tan, Donald C. Wunsch, Danil V. Prokhorov 2018 Missouri University of Science and Technology

Conservative Thirty Calendar Day Stock Prediction Using A Probabilistic Neural Network, H. Tan, Donald C. Wunsch, Danil V. Prokhorov

Donald C. Wunsch

We describe a system that predicts significant short-term price movement in a single stock utilizing conservative strategies. We use preprocessing techniques, then train a probabilistic neural network to predict only price gains large enough to create a significant profit opportunity. Our primary objective is to limit false predictions (known in the pattern recognition literature as false alarms). False alarms are more significant than missed opportunities, because false alarms acted upon lead to losses. We can achieve false alarm rates as low as 5.7% with the correct system design and parameterization.


Computational Intelligence Meets The Netflix Prize, Ryan J. Meuth, Paul Robinette, Donald C. Wunsch 2018 Missouri University of Science and Technology

Computational Intelligence Meets The Netflix Prize, Ryan J. Meuth, Paul Robinette, Donald C. Wunsch

Donald C. Wunsch

The NetFlix Prize is a research contest that will award $1 Million to the first group to improve NetFlix's movie recommendation system by 10%. Contestants are given a dataset containing the movie rating histories of customers for movies. From this data, a processing scheme must be developed that can predict how a customer will rate a given movie on a scale of 1 to 5. An architecture is presented that utilizes the Fuzzy-Adaptive Resonance Theory clustering method to create an interesting set of data attributes that are input to a neural network for mapping to a classification.


Comparison Of Heuristic Dynamic Programming And Dual Heuristic Programming Adaptive Critics For Neurocontrol Of A Turbogenerator, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Ronald G. Harley 2018 Missouri University of Science and Technology

Comparison Of Heuristic Dynamic Programming And Dual Heuristic Programming Adaptive Critics For Neurocontrol Of A Turbogenerator, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Ronald G. Harley

Donald C. Wunsch

This paper presents the design of an optimal neurocontroller that replaces the conventional automatic voltage regulator (AVR) and the turbine governor for a turbogenerator connected to the power grid. The neurocontroller design uses a novel technique based on the adaptive critic designs (ACDs), specifically on heuristic dynamic programming (HDP) and dual heuristic programming (DHP). Results show that both neurocontrollers are robust, but that DHP outperforms HDP or conventional controllers, especially when the system conditions and configuration change. This paper also shows how to design optimal neurocontrollers for nonlinear systems, such as turbogenerators, without having to do continually online training of ...


Clustering Data Of Mixed Categorical And Numerical Type With Unsupervised Feature Learning, Dao Lam, Mingzhen Wei, Donald C. Wunsch 2018 Missouri University of Science and Technology

Clustering Data Of Mixed Categorical And Numerical Type With Unsupervised Feature Learning, Dao Lam, Mingzhen Wei, Donald C. Wunsch

Donald C. Wunsch

Mixed-type categorical and numerical data are a challenge in many applications. This general area of mixed-type data is among the frontier areas, where computational intelligence approaches are often brittle compared with the capabilities of living creatures. In this paper, unsupervised feature learning (UFL) is applied to the mixed-type data to achieve a sparse representation, which makes it easier for clustering algorithms to separate the data. Unlike other UFL methods that work with homogeneous data, such as image and video data, the presented UFL works with the mixed-type data using fuzzy adaptive resonance theory (ART). UFL with fuzzy ART (UFLA) obtains ...


Climbing Fibre Purkinje Cell Twins Are Found, Donald C. Wunsch, Witali L. Dunin-Barkowski, S. N. Markin, L. N. Podladchikova 2018 Missouri University of Science and Technology

Climbing Fibre Purkinje Cell Twins Are Found, Donald C. Wunsch, Witali L. Dunin-Barkowski, S. N. Markin, L. N. Podladchikova

Donald C. Wunsch

At the IJCNN'93 in Nagoya we have pronounced a challenging goal: to get activity patterns of airs of Purkinje cells(PC), controlled with the same climbing fiber (CF), - a CF PC Twins problem Here, for the first time in cerebral studies, CF PC twins have been identified and studied. Several important features of the CF PC Twins activity are demonstrated: (1) High constancy of conduction time of impulses of cells of inferior olives to the targetted PCs, (2) a relatively high failure rate (0.05-0.18) of impulse propagation into terminal branches of CF, (3) a salient difference in ...


Backpropagation Of Accuracy, Donald C. Wunsch, M. Yu Senashova, Alexander N. Gorban 2018 Missouri University of Science and Technology

Backpropagation Of Accuracy, Donald C. Wunsch, M. Yu Senashova, Alexander N. Gorban

Donald C. Wunsch

We solve the problem: how to determine maximal allowable errors, possible for signals and parameters of each element of a network, proceeding from the condition that the vector of output signals of the network should be calculated with given accuracy? "Backpropagation of accuracy" is developed to solve this problem


Approximate Dynamic Programming And Neural Networks On Game Hardware, Ryan J. Meuth, Donald C. Wunsch 2018 Missouri University of Science and Technology

Approximate Dynamic Programming And Neural Networks On Game Hardware, Ryan J. Meuth, Donald C. Wunsch

Donald C. Wunsch

Modern graphics processing units (GPU) and game consoles are used for much more than simply 3D graphics applications and video games. From machine vision to finite element analysis, GPU's are being used in diverse applications, collectively called General Purpose computation onf graphics processor units (GPGPU). Additionally, game consoles are entering the market of high performance computing as inexpensive nodes in computing clusters. This paper explores the capabilities and limitations of modern GPU's and game consoles, surveying the ADP and neural network technologies that can be applied to these devices.


Applications Of Diffusion Maps In Gene Expression Data-Based Cancer Diagnosis Analysis, Rui Xu, Donald C. Wunsch, Steven Damelin 2018 Missouri University of Science and Technology

Applications Of Diffusion Maps In Gene Expression Data-Based Cancer Diagnosis Analysis, Rui Xu, Donald C. Wunsch, Steven Damelin

Donald C. Wunsch

Early detection of a tumor's site of origin is particularly important for cancer diagnosis and treatment. The employment of gene expression profiles for different cancer types or subtypes has already shown significant advantages over traditional cancer classification methods. One of the major problems in cancer type recognition-oriented gene expression data analysis is the overwhelming number of measures of gene expression levels versus the small number of samples, which causes the curse of dimension issue. Here, we use diffusion maps, which interpret the eigenfunctions of Markov matrices as a system of coordinates on the original data set in order to ...


An Optoelectronic Implementation Of The Adaptive Resonance Neural Network, Donald C. Wunsch, T. P. Caudell, R. J. Marks, R. A. Falk, C. David Capps 2018 Missouri University of Science and Technology

An Optoelectronic Implementation Of The Adaptive Resonance Neural Network, Donald C. Wunsch, T. P. Caudell, R. J. Marks, R. A. Falk, C. David Capps

Donald C. Wunsch

A solution to the problem of implementation of the adaptive resonance theory (ART) of neural networks that uses an optical correlator which allows the large body of correlator research to be leveraged in the implementation of ART is presented. The implementation takes advantage of the fact that one ART-based architecture, known as ART1, can be broken into several parts, some of which are better to implement in parallel. The control structure of ART, often regarded as its most complex part, is actually not very time consuming and can be done in electronics. The bottom-up and top-down gated pathways, however, are ...


An Optoelectronic Adaptive Resonance Unit, Donald C. Wunsch, T. P. Caudell, R. A. Falk, C. David Capps 2018 Missouri University of Science and Technology

An Optoelectronic Adaptive Resonance Unit, Donald C. Wunsch, T. P. Caudell, R. A. Falk, C. David Capps

Donald C. Wunsch

The authors demonstrate a hardware implementation of the adaptive resonance theory ART 1 neural network architecture. The optoelectronic ART1 unit, is a novel application of an old device. This device-the 4-f or Van der Lugt correlator-has historically been used as a fast pattern classifier. Usually the correlation operation is employed as a matched filter, so that a maximum correlation peak corresponds to a well-matched pattern. The device described also uses the large peaks, but takes specific advantage of the fact that a zero-shift correlation is mathematically equivalent to a two-dimensional inner product. The authors describe a promising method for emulating ...


An Optical Implementation Of Adaptive Resonance Utilizing Phase Conjugation, Donald C. Wunsch, T. P. Caudell, D. J. Morris, R. A. Falk 2018 Missouri University of Science and Technology

An Optical Implementation Of Adaptive Resonance Utilizing Phase Conjugation, Donald C. Wunsch, T. P. Caudell, D. J. Morris, R. A. Falk

Donald C. Wunsch

A novel adaptive resonance theory (ART) device has been conceived that is fully optical in the input-output processing path. This device is based on holographic information processing in a phase-conjugating crystal. This sets up an associative pattern retrieval in a resonating loop utilizing angle-multiplexed reference beams for pattern classification. A reset mechanism is used to reject any given beam, allowing an ART search strategy. The design is similar to that of an existing nonlearning optical associative memory, but is does allow learning and makes use of information the other device discards. This new device is expected to offer higher information ...


An Optical Adaptive Resonance Neural Network Utilizing Phase Conjugation, Donald C. Wunsch, D. J. Morris, T. P. Caudell, R. A. Falk 2018 Missouri University of Science and Technology

An Optical Adaptive Resonance Neural Network Utilizing Phase Conjugation, Donald C. Wunsch, D. J. Morris, T. P. Caudell, R. A. Falk

Donald C. Wunsch

An adaptive resonance (ART) device has been conceived that is fully optical in the input-output processing path. It is based on holographic information processing in a phase-conjugating crystal. This sets up an associative pattern retrieval in a resonating loop utilizing angle-multiplexed reference beams for pattern classification. A reset mechanism is used to reject any given beam, allowing an ART search strategy. The design is similar to an existing nonlearning optical associative memory, but it does allow learning and makes use of information the other device discards. This device is expected to offer higher information storage density than alternative ART implementations.


An Extended Kalman Filter (Ekf) Approach On Fuzzy System Optimization Problem, Nian Zhang, Donald C. Wunsch 2018 Missouri University of Science and Technology

An Extended Kalman Filter (Ekf) Approach On Fuzzy System Optimization Problem, Nian Zhang, Donald C. Wunsch

Donald C. Wunsch

Optimizing the membership functions of a fuzzy system can be viewed as a system identification problem for a nonlinear dynamic system. Basically, we can view the optimization of fuzzy membership functions as a weighted least-squares minimization problem, where the error vector is the difference between the fuzzy system outputs and the target values for those outputs. The extended Kalman filter algorithm is a good choice to solve this system identification problem, not only because it is a derivative-based algorithm that is suitable to solve the weighted least-squares minimization problem, but also because of its appealing predictor-corrector feature for nonlinear system ...


An Industrial Application To Neural Networks To Reusable Design, Donald C. Wunsch, R. Escobedo, T. P. Caudell, S. D. G. Smith, G. C. Johnson 2018 Missouri University of Science and Technology

An Industrial Application To Neural Networks To Reusable Design, Donald C. Wunsch, R. Escobedo, T. P. Caudell, S. D. G. Smith, G. C. Johnson

Donald C. Wunsch

Summary form only given, as follows. The feasibility of training an adaptive resonance theory (ART-1) network to first cluster aircraft parts into families, and then to recall the most similar family when presented a new part has been demonstrated, ART-1 networks were used to adaptively group similar input vectors. The inputs to the network were generated directly from computer-aided designs of the parts and consist of binary vectors which represent bit maps of the features of the parts. This application, referred to as group technology, is of large practical value to industry, making it possible to avoid duplication of design ...


An Embedded Real-Time Neuro-Fuzzy Controller For Mobile Robot Navigation, Nian Zhang, Daryl G. Beetner, Donald C. Wunsch, B. Hemmelman, Ahmad Hasan 2018 Missouri University of Science and Technology

An Embedded Real-Time Neuro-Fuzzy Controller For Mobile Robot Navigation, Nian Zhang, Daryl G. Beetner, Donald C. Wunsch, B. Hemmelman, Ahmad Hasan

Donald C. Wunsch

A reactive fuzzy logic based control strategy was developed for mobile robot navigation. To decrease the number of fuzzy rules and related processing, a RAM-based neural network was combined with the fuzzy logic strategy. The fuzzy rules are used to interpret sensor information. The neural network uses results from the fuzzy logic as well as environmental information to make navigation decisions. The feasibility of this neuro-fuzzy approach was demonstrated on a mobile robot using a simple, 8-bit microcontroller. Experiments show the approach works well, as the robot was able to successfully avoid objects while seeking a goal in real-time. The ...


Aircraft Cabin Noise Minimization Via Neural Network Inverse Model, Xiao Hu, G. Clark, M. Travis, J. L. Vian, Donald C. Wunsch 2018 Missouri University of Science and Technology

Aircraft Cabin Noise Minimization Via Neural Network Inverse Model, Xiao Hu, G. Clark, M. Travis, J. L. Vian, Donald C. Wunsch

Donald C. Wunsch

This paper describes research to investigate an artificial neural network (ANN) approach to minimize aircraft cabin noise in flight. The ANN approach is shown to be able to accurately model the non-linear relationships between engine unbalance, airframe vibration, and cabin noise to overcome limitations associated with traditional linear influence coefficient methods. ANN system inverse models are developed using engine test-stand vibration data and on-airplane vibration and noise data supplemented with influence coefficient empirical data. The inverse models are able to determine balance solutions that satisfy cabin noise specifications. The accuracy of the ANN model with respect to the real system ...


Adaptive Neural Network Identifiers For Effective Control Of Turbogenerators In A Multimachine Power System, Ganesh K. Venayagamoorthy, Ronald G. Harley, Donald C. Wunsch 2018 Missouri University of Science and Technology

Adaptive Neural Network Identifiers For Effective Control Of Turbogenerators In A Multimachine Power System, Ganesh K. Venayagamoorthy, Ronald G. Harley, Donald C. Wunsch

Donald C. Wunsch

This paper provides a novel method for nonlinear identification of multiple turbogenerators in a five-machine 12-bus power system using continually online trained (COT) artificial neural networks (ANNs). Each turbogenerator in the power system is equipped with all adaptive ANN identifier, which is able to identify/model its particular turbogenerator and rest of the network to which it is connected from moment to moment, based on only local measurements. Each adaptive ANN turbogenerator can be used in the design of a nonlinear controller for each turbogenerator in a multimachine power system. Simulation results for the adaptive ANN identifiers are presented


Adaptive Multi-Vehicle Area Coverage Optimization System And Method, Ryan J. Meuth, John Lyle Vian, Emad W. Saad, Donald C. Wunsch 2018 Missouri University of Science and Technology

Adaptive Multi-Vehicle Area Coverage Optimization System And Method, Ryan J. Meuth, John Lyle Vian, Emad W. Saad, Donald C. Wunsch

Donald C. Wunsch

A system and method for dividing a predefined search region into a map of a plurality of subregions to be searched by a plurality of mobile platforms, taking into account the capabilities of the mobile platforms and varying environmental conditions within the subregions, while minimizing the time needed to search each of the subregions. The system and method updates the map of the subregions as needed, in real time, to account for changing environmental conditions and changes in the capabilities of the mobile platforms being used. The subregions may also be determined using a desired level of probability for detecting ...


Adaptive Multi-Vehicle Area Coverage Optimization System And Method, Ryan J. Meuth, John Lyle Vian, Emad W. Saad, Donald C. Wunsch 2018 Missouri University of Science and Technology

Adaptive Multi-Vehicle Area Coverage Optimization System And Method, Ryan J. Meuth, John Lyle Vian, Emad W. Saad, Donald C. Wunsch

Donald C. Wunsch

A mission planning system for determining an optimum use of a plurality of vehicles in searching a predefined geographic area (PGA). A discretizer subsystem may be used for sensing the capabilities of each vehicle to produce a point set defining a number of points within the PGA that the vehicles must traverse to completely search the PGA. A task allocator subsystem may determine an optimum division of the PGA into different subregions to be handled by specific ones of the vehicles, thus to minimize an overall time needed to search the PGA. A path optimizer subsystem may determine an optimum ...


Adaptive Critic Designs, Danil V. Prokhorov, Donald C. Wunsch 2018 Missouri University of Science and Technology

Adaptive Critic Designs, Danil V. Prokhorov, Donald C. Wunsch

Donald C. Wunsch

We discuss a variety of adaptive critic designs (ACDs) for neurocontrol. These are suitable for learning in noisy, nonlinear, and nonstationary environments. They have common roots as generalizations of dynamic programming for neural reinforcement learning approaches. Our discussion of these origins leads to an explanation of three design families: heuristic dynamic programming, dual heuristic programming, and globalized dual heuristic programming (GDHP). The main emphasis is on DHP and GDHP as advanced ACDs. We suggest two new modifications of the original GDHP design that are currently the only working implementations of GDHP. They promise to be useful for many engineering applications ...


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