Hierarchical Coordination of Economic Agents (2009)
Markus Feurstein, Martin Natter, Alfred Taudes, Industrielle Informationsverarbeitung, Georg Dorffner
This paper discusses the formation of organizational knowledge of boundedly rational Economic agents and studies the necessity of hierarchical coordination of economic agents. We consider a firm that...
Anticipatory Behaviour based on Prediction of Image Sequences (2009)
Achim Lew, Patrick M. Poelz, Georg Dorffner
Abstract. In our scenario an object moves in an environment with obstacles. We would like to provide a robot with anticipatory behaviour. The target is often not visible and the robot should learn to...
Fat Tails and Non-linearity in Volatility Models: What is more important? (2007)
Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
Since the seminal works of Engle [7] and Bollerslev [3] about heteroskedastic return series models, many extensions of their (G)ARCH models have been proposed in the literature. In particular, the...
Experiences with Neural Networks as a Diagnostic Tool in Medical Image Processing (2007)
Georg Dorffner, Erich Prem, Markus Mackinger, Stefan Kundrat, Paolo Petta, Gerold Porenta, ...
this paper we report about part of this larger project, namely about experiences with applying neural networks to the interpretation of planar thallium-201 scintigrams [4] for the assessment of...
Classification through Hyperplane Fitting with Feedforward Neural Networks (2007)
This paper introduces and demonstrates a novel (or at least unusual) way of using feedforward neural networks for classification, inspired by a technique known from statistics. Usually, hidden units...
Georg Dorffner, Christian Stocklmayer, Christian Schmidt, Heinrich Schima
In this paper we report about the application of multilayer perceptrons to three important tasks in the control of rotary blood pumps, namely the estimation of left atrium pressure, and the...
A Self-Learning Visual Pattern Explorer and Recognizer using a Higher Order Neural Network (2007)
Günter Linhart, Georg Dorffner
Higher order neural networks, although known for their power, have not been acknowledged very much in literature, mainly due to their apparent computational complexity. In this paper a proposal...
Can ICA improve sleep-spindles detection? (2007)
Roman Rosipal, Georg Dorffner, Ernst Trenker
We investigated the possibility to use the Independent Component Analysis as a method for preprocessing the sleep EEG data with the aim to improve detection of sleep spindles - specific phenomena of...
Identifying Stochastic Processes with Mixture Density Networks (2007)
Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
In this paper we investigate the use of mixture density networks (MDNs) for identifying complex stochastic processes. Regular multilayer perceptrons (MLPs), widely used in time series processing,...
Can neural networks improve signal processing? A criticial assessment from the ANNDEE (2007)
Project Georg Dorffner, Georg Dorffner
This paper reports about the critical assessment of neural network applications in the domain of electroencephalography (EEG) processing, which can be considered as an outcome of the EU-project...
When Pseudowords Become Words - Effects of Learning on Orthographic Similarity Priming (2007)
Georg Dorffner, Catherine L. Harris
This paper investigates empirical predictions of a connectionist model of word learning. The model predicts that, although the mapping between word form and meaning is arbitrary (thus rendering words...
Can neural networks improve signal processing? A criticial assessment from the ANNDEE project (2007)
This paper reports about the critical assessment of neural network applications in the domain of electroencephalography (EEG) processing, which can be considered as an outcome of the EU-project...
Georg Dorffner, Erich Prem, Harald Trost
In this paper we present a definition of 'symbol ' in cognitive science which is designed to clear some obvious misunderstandings in discussions around %ymbolic " vs....
Arthur Flexer, Herbert Bauer, Claus Lamm, Georg Dorffner
Abstract. Two model-based techniques, Gaussian Mixture Models with integrated noise component and Principal Component Analysis, are applied to noise reduction for single trial evoked potentials which...
Christian Schittenkopf, Peter Tino, Georg Dorffner
Essentially, there are two notions of volatility in literature: historical volatility and implied volatility. While measures of the former notion are derived from historical returns by (weighted)...
Christian Schittenkopf, Georg Dorffner
One of the central goals in finance is to find better models for pricing and hedging financial derivatives such as call and put options. We present a seminonparametric approach to risk-neutral...
The Effect of Incentive Schemes and Organizational (2007)
Martin Natter, Andreas Mild, Markus Feurstein, Georg Dorffner, Alfred Taudes, In Cooperation
Papers published in this report series are preliminary versions of journal articles and not for quotations. This paper was accepted for publication in:
06231 Executive Summary -- Towards Affordance-based Robot Control (2006)
Rome, Erich, Hertzberg, Joachim, Dorffner, Georg, Doherty, Patrick
This article summarizes the objectives and the program of the Dagstuhl seminar 06231, ``Towards Affordance-based Robot Control''. It was held from June 5 to June 9, 2006, at the International...
06231 Abstracts Collection -- Towards Affordance-Based Robot Control (2006)
Rome, Erich, Doherty, Patrick, Dorffner, Georg, Hertzberg, Joachim
From June 5 to June 9, 2006, the Dagstuhl Seminar 06231 ``Towards Affordance-Based Robot Control'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the...
Simulation and Validation of an Integrated Markets Model (2003)
Sallans, Brian, Pfister, Alexander, Karatzoglou, Alexandros, Dorffner, Georg
The behavior of boundedly rational agents in two interacting markets is investigated. A discrete-time model of coupled financial and consumer markets is described. The integrated model consists of...
Simulation and validation of an integrated markets model (2003)
Sallans, Brian, Pfister, Alexander, Karatzoglou, Alexandros, Dorffner, Georg
The behavior of boundedly rational agents in two interacting markets is investigated. A discrete-time model of coupled financial and consumer markets is described. The integrated model consists of...
A simulation study of managerial compensation (2003)
Sallans, Brian, Pfister, Alexander, Dorffner, Georg
A computational economics model of managerial compensation is presented. Risk-averse managers are simulated, and shown to adopt more risk-taking under the influence of stock options. It is also shown...
Miazhynskaia, Tatiana, Frühwirth-Schnatter, Sylvia, Dorffner, Georg
This paper presents a comprehensive review and comparison of five computational methods for Bayesian model selection, based on MCMC simulations from posterior model parameter distributions. We apply...
Miazhynskaia, Tatiana, Dorffner, Georg, Dockner, Engelbert J.
We used neural-network based modelling to generalize the linear econometric return models and compare their out-of-sample predictive ability in terms of different performance measures under three...
On the economic costs of value at risk forecasts (2003)
Miazhynskaia, Tatiana, Dockner, Engelbert J., Dorffner, Georg
We specify a class of non-linear and non-Gaussian models for which we estimate and forecast the conditional distributions with daily frequency. We use these forecasts to calculate VaR measures for...
Tatiana Miazhynskaia, Sylvia Frühwirth-schnatter, Georg Dorffner, In Cooperation, Tatiana Miazhynskaia, Sylvia Frühwirth-schnatter, ...
Papers published in this report series are preliminary versions of journal articles and not for quotations.
Tatiana Miazhynskaia, Georg Dorffner, Engelbert J. Dockner, In Cooperation, Tatiana Miazhynskaia, Georg Dorffner, ...
Papers published in this report series are preliminary versions of journal articles and not for quotations.
Economics and Management Science’). On the Economic Costs of Value at Risk Forecasts (2003)
Tatiana Miazhynskaia, Engelbert J. Dockner, Georg Dorffner, In Cooperation, Tatiana Miazhynskaia, Engelbert J. Dockner, ...
Papers published in this report series are preliminary versions of journal articles and not for quotations.
Using ICA for Removal of Ocular Artifacts in EEG Recorded from Blind Subjects (2003)
Arthur Flexer, Herbert Bauer, Jürgen Prip, Georg Dorffner
One of the standard applications of Independent Component Analysis (ICA) to EEG is removal of artifacts due to movements of the eye bulbs. Short blinks as well as slower saccadic movements are...
The dynamics of interacting markets (2002)
Sallans, Brian, Dorffner, Georg, Karatzoglou, Alexandros
The behavior of boundedly rational agents in two interacting markets is investigated. A discrete-time model of coupled financial and consumer markets is described. The integrated model is then used...
Growing event memories for autonomous robots (2002)
Erich Prem, Erik Hörtnagl, Georg Dorffner
Abstract. The aim of this paper is to provide a systematic overview of methods that are potentially useful for growing event memories in autonomous robots. Recognizing events in sequences of sensor...
Continuous Unsupervised Sleep Staging Based on a single EEG signal (2002)
Arthur Flexer, Georg Gruber, Georg Dorffner
We report improvements on automatic continuous sleep staging using Hidden Markov Models (HMM). Our totally unsupervised approach detects the cornerstones of human sleep (wakefulness, deep and rem...
The Dynamics of Interacting Markets: First Results (2002)
Brian Sallans, Brian Sallans, Georg Dorffner, Alexandros Karatzoglou, Brian Sallans, ...
The behavior of boundedly rational agents in two interacting markets is investigated. A discrete-time model of coupled financial and consumer markets is described. The integrated model is then used...
Natter, Martin, Mild, Andreas, Feurstein, Markus, Dorffner, Georg, Taudes, Alfred
This paper proposes a new model for studying the new product development process in an artificial environment. We show how connectionist models can be used to simulate the adaptive nature of agents...
Arthur Flexer, Herbert Bauer, Claus Lamm, Georg Dorffner
Abstract. Gaussian Mixture Models with integrated noise component are a method developed for speech analysis to estimate signals hidden in background noise. We apply this technique to estimate single...
On nonlinear, stochastic dynamics in economic and financial time series (2001)
Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. However, clear evidence of chaotic structures is usually prevented by large...
On Nonlinear, Stochastic Dynamics in Economic and Financial Time Series (2000)
Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. Evidence of chaotic structures is usually blurred, however, by large random...
On Nonlinear, Stochastic Dynamics in Economic and Financial Time Series (2000)
Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. Evidence of chaotic structures is usually blurred, however, by large random...
On Nonlinear, Stochastic Dynamics in Economic and Financial Time Series (2000)
Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. Evidence of chaotic structures is usually blurred, however, by large random...
On Nonlinear, Stochastic Dynamics in Economic and Financial Time Series (2000)
Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. Evidence of chaotic structures is usually blurred, however, by large random...
The benefit of information reduction for trading strategies (2000)
Schittenkopf, Christian, Tino, Peter, Dorffner, Georg
Motivated by previous findings that discretization of financial time series can effectively filter the data and reduce the noise, this experimental study compares the trading performance of...
Tino, Peter, Schittenkopf, Christian, Dorffner, Georg
In this paper we investigate the potential of the analysis of noisy non-stationary time series by quantizing it into streams of discrete symbols and applying finite-memory symbolic predictors. The...
Risk-neutral density extraction from option prices (2000)
Schittenkopf, Christian, Dorffner, Georg
One of the central goals in finance is to find better models for pricing and hedging financial derivatives such as call and put options. We present a semi-nonparametric approach to risk-neutral...
Georg Dorffner, Christian Schittenkopf
Abstract. We study a novel recurrent network architecture with dynamics of iterative function systems used in chaos game representations of DNA sequences [16, 11]. We show that such networks code the...
The profitability of trading volatility using real-valued and symbolic models (2000)
Christian Schittenkopf, Peter Tino, Georg Dorffner
Essentially, there are two notions of volatility in literature: historical volatility and implied volatility. While measures of the former notion are derived from historical returns by (weighted)...
A Symbolic dynamics approach to volatility prediction (2000)
Peter Tino, Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
We consider the problem of predicting the direction of daily volatility changes in the Dow Jones Industrial Average (DJIA). This is accomplished by quantizing a series of historic volatility changes...
Peter Tino, Christian Schittenkopf, Georg Dorffner
In this paper we investigate the potential of the analysis of noisy non-stationary time series by quantizing it into streams of discrete symbols and applying finitememory symbolic predictors. The...
The Benefit of Information Reduction for Trading Strategies (2000)
Christian Schittenkopf, Peter Tino, Georg Dorffner
Motivated by previous findings that discretization of financial time series can effectively filter the data and reduce the noise, this experimental study compares the trading performance of...
Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
In financial econometrics the modeling of asset return series is closely related to the estimation of the corresponding conditional densities. One reason why one is interested in the whole...
Building predictive models from fractal representations of symbolic sequences (2000)
We propose a novel approach for building finite memory predictive models similar in spirit to variable memory length Markov models (VLMMs). The models are constructed by first transforming then-block...
The tradeoff between coordination and interfering learning signals (1999)
Feurstein, Markus, Natter, Martin, Dorffner, Georg, Taudes, Alfred
This paper discusses the formation of organizational knowledge of boundedly rational Economic agents and studies the necessity of hierarchical coordination of economic agents. We consider a firm that...
New product development in the artificial factory (1999)
Mild, Andreas, Natter, Martin, Trcka, Michael, Feurstein, Markus, Merz, Christian, Taudes, Alfred, ...
We study the product development process in an artificial firm using two different incentive schemes (market share/production costs vs. life cycle return). In the product development process, we...
Forecasting time-dependent conditional densities (1999)
Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
In financial econometrics the modeling of asset return series is closely related to the estimation of the corresponding conditional densities. One reason why one is interested in the whole...
Non-linear versus non-gaussian volatility models (1999)
Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
One of the most challenging topics in financial time series analysis is the modeling of conditional variances of asset returns. Although conditional variances are not directly observable there are...
On non-linear, stochastic dynamics in economic and financial time series (1999)
Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. However, clear evidence of chaotic structures is usually prevented by large...
Non-linear versus non-gaussian volatility models (1999)
Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
One of the most challenging topics in financial time series analysis is the modeling of conditional variances of asset returns. Although conditional variances are not directly observable there are...
A Symbolic Dynamics Approach to Volatility Prediction (1999)
Peter Tino, Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
We consider the problem of predicting the direction of daily volatility changes in the Dow Jones Industrial Average (DJIA). This is accomplished by quantizing a series of historic volatility changes...
On Non-Linear, Stochastic Dynamics in Economic and Financial Time Series (1999)
In Cooperation, Christian Schittenkopf, Christian Schittenkopf, Georg Dorffner, Georg Dorffner, E. Dockner, ...
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. However, clear evidence of chaotic structures is usually prevented by large...
Artefact Processing of the Sleep EEG In The "SIESTA"- Project (1999)
Alois Schlögl, A. Schlgl, Peter Anderer, Manel J. Barbanoj, Georg Gruber, Jose-Luis Lorenzo, ...
: Artefact processing is an important issue in automated analysis of the sleep EEG. Nine artefact types were identified and their frequency of occurrence was analysed in 15 all-night sleep recordings...
Non-linear versus Non-gaussian Volatility Models (1999)
In Cooperation, Christian Schittenkopf, Christian Schittenkopf, Georg Dorffner, Georg Dorffner, Engelbert J. Dockner, ...
One of the most challenging topics in financial time series analysis is the modeling of conditional variances of asset returns. Although conditional variances are not directly observable there are...
Forecasting Time-dependent Conditional Densities: A Neural Network Approach (1999)
Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
In financial econometrics the modeling of asset return series is closely related to the estimation of the corresponding conditional densities. One reason why one is interested in the whole...
Volatility prediction with mixture density networks (1998)
Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
Despite the lack of a precise definition of volatility in finance, the estimation of volatility and its prediction is an important problem. In this paper we compare the performance of standard...
Recurrent neural networks with iterated function systems dynamics (1998)
We suggest a recurrent neural network (RNN) model with a recurrent part corresponding to iterative function systems (IFS) introduced by Barnsley [1] as a fractal image compression mechanism. The key...
Identifying stochastic processes with mixture density networks (1998)
Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
In this paper we investigate the use of mixture density networks (MDNs) for identifying complex stochastic processes. Regular multilayer perceptrons (MLPs), widely used in time series processing,...
Constructing finite-context sources from fractal representations of symbolic sequences (1998)
We propose a novel approach to constructing predictive models on long complex symbolic sequences. The models are constructed by first transforming the training sequence n-block structure into a...
A symbolic dynamics approach to volatility prediction (1998)
Tino, Peter, Schittenkopf, Christian, Dorffner, Georg, Dockner, Engelbert J.
We consider the problem of predicting the direction of daily volatility changes in the Dow Jones Industrial Average (DJIA). This is accomplished by quantizing a series of historic volatility changes...
Recurrent neural networks with Iterated Function Systems dynamics (1998)
We suggest a recurrent neural network (RNN) model with a recurrent part corresponding to iterative function systems (IFS) introduced by Barnsley [1] as a fractal image compression mechanism. The key...
Constructing Finite-Context Sources From Fractal Representations of Symbolic Sequences (1998)
We propose a novel approach to constructing predictive models on long complex symbolic sequences. The models are constructed by first transforming the training sequence n-block structure into a...
Identifying Stochastic Processes with Mixture Density Networks (1998)
Management Science, Christian Schittenkopf, Christian Schittenkopf, Georg Dorffner, Georg Dorffner, Engelbert J. Dockner, ...
In this paper we investigate the use of mixture density networks (MDNs) for identifying complex stochastic processes. Regular multilayer perceptrons (MLPs), widely used in time series processing,...
Volatility Prediction with Mixture Density Networks (1998)
Management Science, In Cooperation, Christian Schittenkopf, Christian Schittenkopf, Georg Dorffner, Georg Dorffner, ...
Despite the lack of a precise definition of volatility in finance, the estimation of volatility and its prediction is an important problem. In this paper we compare the performance of standard...
Roman Rosipal, Roman Rosipal, Georg Dorffner, Georg Dorffner
We investigated the possibility to use the Independent Component Analysis (ICA) as a method for preprocessing the sleep EEG data with the aim to improve detection of sleep spindles - specific...
Neural Networks for Recognizing Patterns in Cardiotocograms (1998)
In Cardiotocograms, Claudia Ulbricht, Georg Dorffner, Andreas Lee
The cardiotocogram (CTG) is commonly used for routine fetal monitoring in the delivery room. A major problem is that the interpretation of the CTG trace requires experienced specialists. In order to...
Constructing Finite-Context Sources From Fractal Representations of Symbolic Sequences (1998)
Peter Tino Georg, Georg Dorffner
We propose a novel approach to constructing predictive models on long complex symbolic sequences. The models are constructed by first transforming the training sequence n-block structure into a...
Recurrent neural networks with Iterated Function Systems dynamics (1998)
Peter Tino Georg, Georg Dorffner
We suggest a recurrent neural network (RNN) model with a recurrent part corresponding to iterative function systems (IFS) introduced by Barnsley [1] as a fractal image compression mechanism. The key...
Volatility Prediction with Mixture Density Networks (1998)
Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
Despite the lack of a precise definition of volatility in finance, the estimation of volatility and its prediction is an important problem. In this paper we compare the performance of standard...
Experiences with Bayesian Learning in a Real World Application (1998)
Peter Sykacek, Georg Dorffner, Peter Rappelsberger, Josef Zeitlhofer
This paper reports about an application of Bayes' inferred neural network classifiers to the field of automatic sleep staging. Up to our current knowledge this is one of the first real world...
Manfred Hallas, Georg Dorffner
This paper reports about a comparative study on several linear and nonlinear feedforward and recurrent neural networks trained on artificially created time series. This has lead to interesting...
Constructing Finite-Context Sources From Fractal Representations of Symbolic Sequences (1998)
We propose a novel approach to constructing predictive models on long complex symbolic sequences. The models are constructed by first transforming the training sequence n-block structure into a...
Categorization in Early Language Acquisition - Accounts From a Connectionist Model (1996)
In this paper we introduce a connectionist model for early word learning as an important part of language acquisition. In the spirit of previous connectionist models (e.g. [Plunkett et al. 1993]) we...
A Connectionist Model of Categorization and Grounded Word Learning (1996)
Georg Dorffner, Michael Hentze, Georg Thurner
This paper reports about ongoing research on a connectionist model of the learning of single words and their meaning, grounded in perception. Similar to (Plunkett, Sinha, Moller, & Strandsby,...
Forecasting Fetal Heartbeats with Neural Networks (1996)
Claudia Ulbricht, Georg Dorffner, Andreas Lee
The given task is to forecast the intervals between the heartbeats recorded from a fetus. The six tested neural network models combine input windows, hidden layer feedback, and self-recurrent unit...
Neural Networks for Time Series Processing (1996)
This paper provides an overview over the most common neural network types for time series processing, i.e. pattern recognition and forecasting in spatio-temporal patterns. Emphasis is put on the...
Toward Improving Exercise ECG for Detecting Ischemic Heart Disease with Recurrent (1994)
Abstract. This paper reports about a study evaluating the usefulness of neural networks for the early detection of heart disease based on ECG and other measurements during exercise testing [10]. Data...
A Unified Framework for MLPs and RBFNs: Introducing Conic Section Function Networks (1994)
Georg Dorffner Dept, Georg Dorffner
Multilayer Perceptrons (MLP, Werbos 1974, Rumelhart et al. 1986) and Radial Basis Function Networks (RBFN, Broomhead & Lowe 1988, Moody & Darken 1989) probably are the most widely used neural...
A Unified Framework for MLPs and RBFNs: Introducing Conic Section Function Networks (1994)
Multilayer Perceptrons (MLP, Werbos 1974, Rumelhart et al. 1986) and Radial Basis Function Networks (RBFN, Broomhead & Lowe 1988, Moody & Darken 1989) probably are the most widely used neural...
Concept Support as a Method for Programming Neural Networks with Symbolic Knowledge (1993)
Erich Prem, Markus Mackinger, Georg Dorffner
Neural networks are usually seen as obtaining all their knowledge through training on the basis of examples. In many AI applications appropriate for neural networks, however, symbolic knowledge does...
On Using Feedforward Neural Networks for Clinical Diagnostic Tasks (1993)
Georg Dorffner Austrian, Georg Dorffner, Georg Dorffner, Gerold Porenta, Gerold Porenta
In this paper we present an extensive comparison between several feedforward neural network types in the context of a clinical diagnostic task, namely the detection of coronary artery disease (CAD)...
Formal Neural Network Specification and its Implications on Standardization (1993)
Georg Dorffner, Herbert Wiklicky, Erich Prem
This paper introduces a formal framework for describing and specifying neural networks and discusses several important issues with implications for neural network standardization. In particular, a...
Unsupervised Learning Of Simple Speech Production Based On Soft Competitive Learning (1993)
Georg Dorffner, Thomas Schonauer
this paper we present a simple connectionist model for the adaptive sensorymotor loop involved in perceiving and producing speech. At the heart of the production part lies an articulatory model which...
Connectionism, Symbol Grounding, and Autonomous Agents (1993)
In this position paper we would like to lay out our view on the importance of grounding and situatedness for cognitive science. Furthermore we would like to suggest that both aspects become relevant...
On Using Feedforward Neural Networks for Clinical Diagnostic Tasks (1993)
Georg Dorffner, Georg Dorffner, Gerold Porenta, Gerold Porenta
In this paper we present an extensive comparison between several feedforward neural network types in the context of a clinical diagnostic task, namely the detection of coronary artery disease (CAD)...
Mechanisms For Handling Sequences With Neural Networks (1992)
Claudia Ulbricht Georg, Georg Dorffner, Didier Guillemyn, Javier Olarte
This paper is intended to give an overview of methods for handling sequences with neural networks. Since many typical neural networks cannot be used for processing temporal information they have to...
Integrating Stress and Intonation into a Concept-to-Speech System (1990)
Georg Dorffner, Ernst Buchberger
Abstract: The paper deals with the integration of intonation algorithms into a concept-to-speech system for German 1). The algorithm for computing the stress hierarchy of a sentence introduced by...
Simulation and Validation of an Integrated Markets Model
Brian Sallans, Alexander Pfister, Alexandros Karatzoglou, Georg Dorffner
The behavior of boundedly rational agents in two interacting markets is investigated. A discrete-time model of coupled financial and consumer markets is described. The integrated model consists of...
Bayesian testing for non-linearity in volatility modeling
Miazhynskaia, Tatiana, Fruhwirth-Schnatter, Sylvia, Dorffner, Georg
The Benefit of Information Reduction for Trading Strategies.
Schittenkopf, Christian, Tino, Peter, Dorffner, Georg
Motivated by previous findings that discretization of financial time series can effectively filter the data and reduce the noise, this experimental study compares the trading performance of...
On Nonlinear, Stochastic Dynamics in Economic and Financial Time Series
Christian Schittenkopf, Georg Dorffner, Engelbert Dockner
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. Evidence of chaotic structures is usually blurred, however, by large random...
On Nonlinear, Stochastic Dynamics in Economic and Financial Time Series
Christian Schittenkopf, Georg Dorffner, Engelbert Dockner
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. Evidence of chaotic structures is usually blurred, however, by large random...
On Nonlinear, Stochastic Dynamics in Economic and Financial Time Series
Christian Schittenkopf, Georg Dorffner, Engelbert J. Dockner
The search for deterministic chaos in economic and financial time series has attracted much interest over the past decade. Evidence of chaotic structures is usually blurred, however, by large random...